Hypothetical Situations Research Articles

Is This the End of Anthropology as We Know It? Some Implication of FAIR Principles on Tales in Ethnological and Anthropological Qualitative Research

Open science, accessibility and knowledge sharing, especially of articles and monographs stemming from publicly funded research, seem to be moving in quite a positive direction toward scientific development and have received almost unanimous approval from the scientific community. However, when it comes to data sharing, the existing practice reveals a different picture, and not exclusively a discipline-dependent one. FAIR principles are developed and promoted as guiding tools for creating contextualized standards. The fact that data obtained by a qualitative methodology deserve special attention and treatment regarding the accessibility principle is recognized. Although FAIR principles provide ways to anonymize the data and interlocutors, individuals coming from smaller communities or even communities of practice can sometimes be easily recognized by members of the same community if data are openly accessed. Sometimes the interlocutors might agree with these terms, but sometimes they do not. According to the disciplinary code of ethics, a researcher is obliged to thoroughly describe the ways of the raw data management and usage, and in the case of mandatory raw data sharing (e.g., for receiving funding), it can inevitably impact the narratives collected. The prerogative to make all data open inevitably leads to autocensorship among interlocutors, i.e., resulting in a kind of FAIRy tale being collected. The article discusses the results obtained from the survey carried out among Croatian ethnologists and cultural anthropologists about the currently practiced data sharing, their attitudes about data sharing and their perceived behavior in hypothetical situations connected with data sharing. The results show mixed opinions about data sharing and a desire to follow the disciplinary code of ethics first, i.e., to follow the interlocutors’ wishes in the case of data management and usage.

Another Look at the Security Analysis of the Modulus N = p2q by Utilizing an Approximation Approach for ϕ(N)

Newly developed techniques have been recently documented, which capitalize on the security provided by prime power modulus denoted as N = prqs where2 ≤ s < r. Previousresearchprimarilyconcentrated on the factorization of the modulus of type at minimum N = p3q2. In contrast, within the context of 2 ≤ s < r, we address scenarios in the modulus N = p2q (i.e. r = 2 and s = 1) still need to be covered, showing a significant result to the field of study. This work presents two factorization approaches for the multiple moduli Ni = p2 iqi, relying on a good approximation of the Euler’s totient function ϕ(Ni). The initial method for factorization deals with the multiple moduli Ni = p2 iqi derived from m public keys (Ni,ei) and is interconnected through the equation eid − kiϕ(Ni) = 1. In contrast, the second factorization method is associated with the eidi − kϕ(Ni) = 1. By reorganizing the equations as a simultaneous Diophantine approximation problem and implementing the LLL algorithm, it becomes possible to factorize the list of moduli Ni = p2 iqi concurrently, given that the unknowns d, di, k, and ki are suff iciently small. The key difference between our results and the referenced work is that we cover a real-world cryptosystem that uses the modulus N =p2q. In contrast, the previous work covers a hypothetical situation of modulus in the form of N = prqs.

Nonlinear mixed-effects modeling as a method for causal inference to predict exposures under desired within-subject dose titration schemes.

The ICH E9 (R1) guidance and the related estimand framework propose to clearly define and separate the clinical question of interest formulated as estimand from the estimation method. With that it becomes important to assess the validity of the estimation method and the assumptions that must be made. When going beyond the intention to treat analyses that can rely on randomization, causal inference is usually used to discuss the validity of estimation methods for the estimand of interest. In pharmacometrics, mixed-effects models are routinely used to analyze longitudinal clinical trial data; however, they are rarely discussed as a method for causal inference. Here, we evaluate nonlinear mixed-effects modeling and simulation (NLME M&S) in the context of causal inference as a standardization method for longitudinal data in the presence of confounders. Standardization is a well-known method in causal inference to correct for confounding by analyzing and combining results from subgroups of patients. We show that nonlinear mixed-effects modeling is a particular implementation of standardization that conditions on individual parameters described by the random effects of the mixed-effects model. As an example, we use a simulated clinical trial with within-subject dose titration. Being interested in the outcome of the hypothetical situation that patients adhere to the planned treatment schedule, we put assumptions in a causal diagram. From the causal diagram, conditional independence assumptions are derived either by conditioning on the individual parameters or on earlier outcomes. With both conditional independencies unbiased estimates can be obtained.

Approaches to a crisis in early pregnancy: an explorative qualitative study of medical students and doctors in training in Ireland, using a story completion model

A crisis in early pregnancy can be due to an unplanned pregnancy or a suspected abnormality. Pregnant people have the right to unbiased and comprehensive advice of all options from healthcare providers. Using story completion models (SCM), the aim of this qualitative study was to explore the attitudes of medical students and doctors in training towards crisis pregnancy, specifically two scenarios: early unplanned pregnancy and fatal fetal abnormality (anencephaly). Participants were invited from medical students attending University College Dublin (UCD) and trainees in Obstetrics and Gynaecology in the Royal College of Physicians of Ireland (RCPI) from July to December 2022. SCM involve giving the consenting participant an introduction to a hypothetical situation that acts as the beginning of a story and asking them to complete it. Stories were compiled and analysed using thematic analysis. Research Ethics Committee approval was given by both UCD and the RCPI. The standards for reporting of qualitative research guidelines were followed. Eight doctors in training and six medical students consented to participate in the study; all but two medical students completed both stories to the required word count, giving 25 stories for analysis. For both situations, stories described a variety of approaches, all of which were based on the person, or couples wishes, from continuing in pregnancy to deciding to end the pregnancy. SCM allowed detailed analysis of potentially sensitive subjects such as pregnancy options. This study showed that participating medical students and doctors in training recognise that pregnant people have the right to all choices in crisis pregnancy.

Transparent Corruption: The Effect of Illicit Connections and Trusted References on the Demand for Bureaucratic Intermediation

Abstract This article investigates the effect of priming the existence of corrupt connections to the bureaucracy and of trusted references on the demand for intermediary services. We performed an experimental survey with undergraduate students in Caracas, Venezuela. Participants are presented with a hypothetical situation in which they need to obtain the apostille of their professional degrees in order to migrate and are considering whether to hire an intermediary (“gestor”) or not. The survey randomly reveals the existence of an illicit connection between the gestor and the bureaucracy and whether a trusted individual referred the intermediary. Our findings are not consistent with the “market maker” hypothesis that revealing the existence of illicit connections increases demand. Consistent with the view that trust is a key element in inherently opaque transactions, we find that the demand for intermediaries is price inelastic when gestores are referred by trusted individuals.

Evaluating survey techniques in wastewater-based epidemiology for accurate COVID-19 incidence estimation

Wastewater-based epidemiology (WBE) requires high-quality survey methods to determine the incidence of infections in wastewater catchment areas. In this study, the wastewater survey methods necessary for comprehending the incidence of infection by WBE are clarified. This clarification is based on the correlation with the number of confirmed coronavirus disease 2019 (COVID-19) cases, considering factors such as handling non-detect data, calculation method for representative values, analytical sensitivity, analytical reproducibility, sampling frequency, and survey duration. Data collected from 15 samples per week for two and a half years using a highly accurate analysis method were regarded as gold standard data, and the correlation between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater and confirmed COVID-19 cases was analyzed by Monte Carlo simulation under the hypothetical situation where the quality of the wastewater survey method was reduced. Regarding data handling, it was appropriate to replace non-detect data with estimates based on distribution, and to use geometric means to calculate representative values. For the analysis of SARS-CoV-2 RNA in samples, using a highly sensitive and reproducible method (non-detect rates of <40 %; ≤0.4 standard deviation) and surveying at least three samples, preferably five samples, per week were considered desirable. Furthermore, conducting the survey over a period of time that included at least 50 weeks was necessary. A WBE that meets these survey criteria is sufficient for the determination of the COVID-19 infection incidence in the catchment. Furthermore, WBE can offer additional insights into infection rates in the catchment, such as the estimated 48 % decrease in confirmed COVID-19 cases visiting a clinic following a COVID-19 legal reclassification in Japan.

What's a parent to do? Measuring cultural logics of parenting with computational text analysis

Leading theories on parenting in the United States suggest that parenting varies widely by socioeconomic status, with middle-class parents practicing “concerted cultivation”—marked by parents' intensive efforts to foster their children's development—and working-class parents engaging in the “accomplishment of natural growth”—with children given more freedom to manage their own time. While frequently inferred that these parenting practices reflect different cultural logics of parenting, such logics are inherently hard to measure. Our paper proposes a new inductive way to study parenting logics using computational text analysis applied to a nationally representative survey where respondents provided parenting advice across three hypothetical parenting situations. Analyzing this advice using Biterm Topic Modeling we find that nearly all parenting logics reflect some form of intensive parenting, but within that are multiple nuanced versions varying across two dimensions: (1) assertive vs negotiated parenting, and (2) pedagogic vs pragmatic parenting. Using fractional multinomial logistic regression, we find little difference in how parenting logics vary by race/ethnicity, education, and income, suggesting more similarity across groups and more variability within groups than commonly understood. These findings also demonstrate how computational techniques may provide complementary tools to enrich the study of long-standing questions in social science research, at times offering an analytical naïveté that human coding cannot offer.

Conceptual design of tailings dam and stability assessment

This work aims to present and discuss a conceptual project of mining tailings dam. Therefore, specific topics on tailings dams are visited and the characterization of materials constituting such structure is reviewed in the literature. Based on parameters available in the literature, a hypothetical dam was schematized and its stability was assessed via computational analysis (limit equilibrium and finite element flow analysis). Assessing eventual design changes (additional dam heightening) and hypothetical situations (collapses in the internal drainage), it is concluded that the schematic conceptual design presents itself viable and stable given the proposed geometry and the properties of materials considered. The importance of the internal drainage system for the dam´s stability was also identified.

Socio-techno-economic-environmental investigation of scenarios-based combination sources of green energy system - A case study in Spain

The importance of development, generation, enhancement, and integration of renewable energy sources into the current energy network is excellent; however, the successful implementation of these technologies highly relies on the appropriate regulations, type of application, and the careful consideration of social-economic-technical-environmental analysis. In this research, the PRISMI Plus toolkit, which has been proven as a powerful toolkit in PRISMI projects for islands, the dataset provided by the municipality, and the update of the Sustainable Energy Action Plan were utilized for effective techno-economic analysis, comparing the flexibility of renewable energy systems including photovoltaic and wind turbines and planning of renewable energy scenarios of “Onda” town, in eastern Spain. The examined scenarios consist of a baseline scenario, a 50 % share scenario, and a 100 % share scenario. The baseline scenario entails no change in emissions or new installations of renewable energy resources. In contrast, the 50 % share and 100 % reduction in emissions are achieved through the installation of suitable-sized renewable energy sources, respectively. In scenarios 2 and 3, Electric Vehicles (EVs) are considered to be restricted to smart charging functionality only, and no Vehicle-To-Grid (V2G) is allowed. Based on the techno-socio-economic assessment, the second scenario has a more extensive technical capability to investment ratio compared to the other scenarios. Therefore, the 50 % share scenario is considered more worthwhile. This hypothetical situation has the potential to decrease energy costs by as much as 10 %, diminish relying on fossil fuels for electricity production, confine Greenhouse Gas (GHG) emissions, generate employment opportunities at the local level, and guide the municipality towards the ideals of a sustainable and energy self-sufficient city. Although similar research has been done for other cities, the novelty of this research is in the health consideration.

Parent capability: A factorial survey experiment on the duration of parental leave

We use Sen’s capability approach to identify factors able to increase the effective freedom of working parents when deciding the length of their parental leave. We conducted a factorial survey experiment (FSE) with a Spanish sample of employees aged between 25 and 45. Respondents were asked to imagine that they were first-time parents and several descriptions of hypothetical situations or vignettes (where aspects of the leave system, workplace and family environment were randomly varied) were presented to them. Our goal was to identify the causal effect of a number of dimensions on their hypothetical decisions about the total number of weeks they would be on parental leave. A longer statutory duration and a higher replacement rate (of the paid part of the leave), having job security, and a workplace with friendly practices and cultures, were found to have a significant positive impact on the duration of parental leave.

Wildfire-smoke-precipitation interactions in Siberia: Insights from a regional model study

Powerful wildfires occurring in Siberia each summer emit large amounts of smoke aerosol that, according to studies of the environmental impacts of biomass burning (BB) aerosol in different regions of the world, can affect precipitation and other weather parameters and induce feedback on fires. However, the knowledge of smoke-weather interactions and fire-weather feedback in Siberia is presently limited. To advance this knowledge, we performed coupled-meteorology-chemistry simulations of aerosols and weather in a Siberian region covering taiga and tundra using the CHIMERE chemistry-transport model and the WRF meteorological model. We addressed a monthly period of July 2016 and considered several modeling scenarios in which aerosol-radiation interaction (ARI) and aerosol-cloud interaction (ACI) were taken into account jointly or separately. The simulation results were combined with emission and precipitation data retrieved from satellite observations. The joint analysis of the simulated precipitation fields and satellite-observation-based data revealed that in the taiga, the inhibiting effect of Siberian smoke on precipitation induced a significant positive feedback on BB aerosol emissions that, according to our estimates, enhanced by 27 (±7) % respective to a hypothetical situation in which smoke-weather interactions were absent. At the same time, an increase of precipitation over active fire spots due to ACI and ARI in tundra led to the formation of a negative feedback loop between fire emissions and BB smoke, resulting in a reduction of BB aerosol emissions there by 14 (±6) %. Hence, this study revealed evidence for significant feedback of smoke-induced precipitation changes on fire emissions in Siberia. Given the global importance of Siberia as a major carbon sink, this feedback needs to be studied further and accurately taken into account in projections of climate change both on regional and global scales.

Liability for AI-related IP infringements in the European Union

Abstract As Artificial Intelligence (AI) technology develops and more AI systems are put on the market, concern about the implications of such AI systems on humans is growing. A particular area of concern is the impact of AI systems on intellectual property rights (IPRs) as infringement might occur in relation to the use of AI systems. IPR infringements can be committed by training an AI system, as well as by using or when operating an AI system. This raises the question of liability for such IPR infringements. This research covers situations where IPR infringements are committed by training an AI system, as well as those where infringements are committed by using or operating an AI system. One hypothetical situation of an AI system created solely for the purpose of infringing IPRs is investigated, but also includes situations where otherwise legitimate AI systems are misused in criminal activities as tools for the production and sale of infringing goods. These areas are analysed in relation to the proposed AI Liability Directive and other relevant European Union legislation to identify what rules would be applicable to liability for damage in such cases. The research also considers the recently enacted AI Act. In instances where the damage is caused by AI-enabled products and services, the study shows how the ‘rebuttable presumption of causality’ provided for under the AI Liability Directive could be applied.

Do patients prefer a human doctor, artificial intelligence, or a blend, and is this preference dependent on medical discipline? Empirical evidence and implications for medical practice.

Today the doctor-patient relationship typically takes place in a face-to-face setting. However, with the advent of artificial intelligence (AI) systems, two further interaction scenarios are possible: an AI system supports the doctor's decision regarding diagnosis and/or treatment while interacting with the patient, or an AI system could even substitute the doctor and hence a patient interacts with a chatbot (i.e., a machine) alone. Against this background, we report on an online experiment in which we analyzed data from N = 1,183 people. The data was collected in German-speaking countries (Germany, Austria, Switzerland). The participants were asked to imagine they had been suffering from medical conditions of unknown origin for some time and that they were therefore visiting a health center to seek advice from a doctor. We developed descriptions of patient-doctor interactions (referred to as vignettes), thereby manipulating the patient's interaction partner: (i) human doctor, (ii) human doctor with an AI system, and (iii) an AI system only (i.e., chatbot). Furthermore, we manipulated medical discipline: (i) cardiology, (ii) orthopedics, (iii) dermatology, and (iv) psychiatry. Based on this 3 × 4 experimental within-subjects design, our results indicate that people prefer a human doctor, followed by a human doctor with an AI system, and an AI system alone came in last place. Specifically, based on these 12 hypothetical interaction situations, we found a significant main effect of a patient's interaction partner on trust, distrust, perceived privacy invasion, information disclosure, treatment adherence, and satisfaction. Moreover, perceptions of trust, distrust, and privacy invasion predicted information disclosure, treatment adherence, and satisfaction as a function of interaction partner and medical discipline. We found that the situation in psychiatry is different from the other three disciplines. Specifically, the six outcome variables differed strongly between psychiatry and the three other disciplines in the "human doctor with an AI system" condition, while this effect was not that strong in the other conditions (human doctor, chatbot). These findings have important implications for the use of AI in medical care and in the interaction between patients and their doctors.

Epidemiological impact of revoking mask-wearing recommendation on COVID-19 transmission in Tokyo, Japan

Despite the global implementation of COVID-19 mitigation measures, the disease continues to maintain transmission. Although mask wearing became one of the key measures for preventing the transmission of COVID-19 early in the pandemic period, many countries have relaxed the mandatory or recommended wearing of masks. The objective of the present study was to estimate the epidemiological impact of removing the mask-wearing recommendation in Japan. We developed a model to assess the consequences of declining mask-wearing coverage after the government revoked its recommendation in February 2023. The declining mask-wearing coverage was estimated using serial cross-sectional data, and a mathematical model was devised to determine the age-specific incidence of COVID-19 using the observed case count in Tokyo from week of October 3, 2022 to October 30, 2023. We explored model-based counterfactual scenarios to measure hypothetical situations in which the mask-wearing coverage decreases or increases relative to the observed coverage. The results show that mask-wearing coverage declined from 97% to 69% by the week of October 30, 2023, and that if the mask-wearing recommendation had continued, 427 lives could have been saved in Tokyo. If the mask-wearing coverage had declined to 25% of the observed level, the model suggests there might have been 1587 additional deaths. Thus, revoking the mask-wearing recommendation had a substantial epidemiological impact. In future pandemics, our proposed approach could provide a real-time quantification of the effects of relaxing countermeasures.

Analyzing the impact of concealed carry weapons and school resource officers on school shootings: An agent-based modeling approach.

This paper presents a simulation modeling study that examines the potential benefit of arming public school staff members with concealed carry weapons (CCWs) in combination with school resource officers (SROs) during active shooter events. By simulating real or hypothetical situations and altering various parameters, simulation modeling allows researchers to explore the potential factors that may influence the outcome of such situations. This study will analyze literature on active shootings to identify key characteristics that may impact the outcome of an event and will use an actual school active shooter event as a basis for developing a simulation model. The researchers will then introduce a CCW carrier and an SRO into the scenario to assess the potential impact and outcomes of such a change. The results of this study may inform the development of effective policies and procedures for addressing active shooter events in public settings.

THE PROBLEM OF MODEL ADEQUACY IN THE APPLICATION OF GAME THEORY IN INTERNATIONAL RELATIONS

The article considers the use of game theory in international relations and the risks associated with it. An analysis is made of the possibility of reflecting the same real situations using different game models with different connotations. The concept of the adequacy of the model in relation to the situation is considered, as well as the necessary logical stage of proving this adequacy and the risk of manipulative influence in the absence of such proof. Attention is paid to the phenomenon of the model itself and its relation to the real object of modeling.The opinion is argued about the need to prove the similarity before using the analogy as an argument for attempts to persuade on the basis of this similarity. The mechanism of manipulation is considered in which, by skipping the discussion of the adequacy of the model, it is automatically considered adequate, so the author of the model can impose his own forecasts on the consumer of information regarding the development of events, as well as his own subjective vision of the positivity of the results.As an example, two well-known problems in game theory are considered, actively used for modeling international relations: the Prisoner's Dilemma and the Chicken game. An example of modeling the same hypothetical situation using both games and differences in subjective perception of the same results, which are manifested in the choice of which of these games to use, is given. The opinion is given that although both games can be very useful in the field of international relations, when consuming information which incorporates these and other games, it is necessary to carefully check not only the author's forecasts regarding the development of events, but also the assessment of the positivity of the results in the model.

Characterisation of the pedagogical knowledge of evolution content using the mapping approach

ABSTRACT The attributes of Pedagogical Content Knowledge (PCK) related to biological evolution in Biology teachers with varying years of professional experience were investigated. Unlike previous research that used questionnaires and interviews, we adopted a mapping approach, a more contemporary exploratory methodology. We conceptualised PCK as a narrative knowledge, which inquiring through a hypothetical classroom situation, reveals a teleological epistemological obstacle about evolution. We explored the perceptions, predictions, and justifications of 32 teachers, using their narratives as analysis units for mapping in accordance with their teaching experience. The results highlight that the most linked components of PCK are knowledge of the curriculum, knowledge of students, and teaching strategies. It was observed that novice teachers exhibit PCK with a greater number of linked components. Conversely, expert teachers recognise assessment knowledge in the structure of PCK, while novices emphasise the purposes and nature of the sciences. These findings suggest that the exploration of the relationships between components should not be viewed uniformly, but in terms of the type of the generating knowledge.

On the characterization of EM emission of electronic products: Case study for different program modes

The characterization of the EM emissions for electronic products is crucial to ensure that the emissions have met the requirements of the EMC standards. For this, a more comprehensive testing is required to get more meaningful results. While, the emergence of non-stationary emissions is a challenge to obtain valid analysis results. So far, non-stationary EM emissions is not considered and treated properly in the emission analysis. This paper presents a new method for the analysis of EM emissions from electronic devices as a case study by testing three different program modes (scenarios) of Intel Galileo board. These program modes were designed to vary processing intensity in its memory and processor. A comparison was also made between the actual situation (the presence of non-stationary signals) and the hypothetical situation with the assumption that all emissions were stationary. As a result, a significant difference was observed when the analysis considered the real scenario of a non-stationary emission. The ratio between the average autocorrelation using the proposed algorithm and the average correlation by ignoring the non-stationarity of the emission signal was 113.6 times. The study concludes that different program modes produce the different characteristics of EM emissions, making some of them non-stationary. Hence, we strongly suggest the consideration of the non-stationarity of the EM emissions in characterizing complex electronic devices.

Stress-strain state of building structures taking into account possible local failure of the element

The issue of choosing a structural design and material for supporting structures is an important technical and economic task at the stage of developing a design solution. It depends on a number of factors: consequence class of the structure, reliability of the design solution, savings in basic building materials. The publication provides a classification of design schemes and types of load-bearing structures used in the corresponding solutions. The disadvantages and advantages of using prefabricated and monolithic structures for the installation and subsequent operation of the structural scheme of buildings and structures are considered. Modern design requirements include ensuring the ability of a damaged structure to adapt to new conditions while continuing to function while ensuring the integrity of human life, property and equipment. New conditions mean the consequences of the occurrence of a certain emergency situation, accompanied by weakening or overloading of the load-bearing structures of a structure or soil foundation: a change in the structural design, a combination of new existing loads and a redistribution of internal forces. The publication reflects the results of assessing the redistribution of the stress-strain state of the elements of the “base - foundations - load-bearing structures” system as a result of the implementation of a hypothetical emergency situation with the exclusion of the load-bearing structure from operation. The case of the collapse of one of the vertical load-bearing elements (local failure of the pylon) of an underground floor, which can be used as a dual-use structure, is considered. Calculations for the stability of the structure against progressive collapse were carried out by numerical modeling in the LIRA SAPR-2019 software using a quasi-static calculation and the method of direct integration of dynamics over time. It has been demonstrated that the method of numerical modeling the joint work of a building with a soil base affects the results of a calculation of the progressive collapse of the building frame. The influence of local collapse of a vertical load-bearing element on the redistribution of stresses and strains in the foundation structures of a building section is assessed. The load on the piles under the pylons around the element removed under the local failure scenario is expected to increase by 15...25%.

Factors influencing U.S. women’s interest and preferences for breast cancer risk communication: a cross-sectional study from a large tertiary care breast imaging center

BackgroundBreast imaging clinics in the United States (U.S.) are increasingly implementing breast cancer risk assessment (BCRA) to align with evolving guideline recommendations but with limited uptake of risk-reduction care. Effectively communicating risk information to women is central to implementation efforts, but remains understudied in the U.S. This study aims to characterize, and identify factors associated with women’s interest in and preferences for breast cancer risk communication.MethodsThis is a cross-sectional survey study of U.S. women presenting for a mammogram between January and March of 2021 at a large, tertiary breast imaging clinic. Survey items assessed women’s interest in knowing their risk and preferences for risk communication if considered to be at high risk in hypothetical situations. Multivariable logistic regression modeling assessed factors associated with women’s interest in knowing their personal risk and preferences for details around exact risk estimates.ResultsAmong 1119 women, 72.7% were interested in knowing their breast cancer risk. If at high risk, 77% preferred to receive their exact risk estimate and preferred verbal (52.9% phone/47% in-person) vs. written (26.5% online/19.5% letter) communications. Adjusted regression analyses found that those with a primary family history of breast cancer were significantly more interested in knowing their risk (OR 1.5, 95% CI 1.0, 2.1, p = 0.04), while those categorized as “more than one race or other” were significantly less interested in knowing their risk (OR 0.4, 95% CI 0.2, 0.9, p = 0.02). Women 60 + years of age were significantly less likely to prefer exact estimates of their risk (OR 0.6, 95% CI 0.5, 0.98, p < 0.01), while women with greater than a high school education were significantly more likely to prefer exact risk estimates (OR 2.5, 95% CI 1.5, 4.2, p < 0.001).ConclusionU.S. women in this study expressed strong interest in knowing their risk and preferred to receive exact risk estimates verbally if found to be at high risk. Sociodemographic and family history influenced women’s interest and preferences for risk communication. Breast imaging centers implementing risk assessment should consider strategies tailored to women’s preferences to increase interest in risk estimates and improve risk communication.