A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians. Methods: Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity. Results: Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively. Conclusion: Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics.

Patient-Centered Adult Cardiovascular Care: A Scientific Statement From the American Heart Association.

Patient-centered care is gaining widespread acceptance by the medical and lay communities and is increasingly recognized as a goal of high-quality health care delivery. Patient-centered care is based on ethical principles and aims at establishing a partnership between the health care team and patient, family member, or both in the care planning and decision-making process. Patient-centered care involves providing respectful care by tailoring management decisions to patients' beliefs, preferences, and values. A collaborative care approach can enhance patient engagement, foster shared decision-making that aligns with patient values and goals, promote more personalized and effective cardiovascular care, and potentially improve patient outcomes. The objective of this scientific statement is to inform health care professionals and stakeholders about the role and impact of patient-centered care in adult cardiovascular medicine. This scientific statement describes the background and rationale for patient-centered care in cardiovascular medicine, provides insight into patient-oriented medication management and patient-reported outcome measures, highlights opportunities and strategies to overcome challenges in patient-centered care, and outlines knowledge gaps and future directions.

Willingness to Pay (WTP) for Newer Treatment Options for Diabetes: A Study Among Patients at a Tertiary Care Centre.

Introduction Type 2 diabetes mellitus (T2DM) poses a substantial burden globally and particularly in India, affecting health, finances, and overall quality of life. The management of this condition relies on lifestyle modifications and advanced pharmacological interventions, with emerging drugs showing promise in areas such as administration, side effects, efficacy, and cardiovascular benefits. However, their market penetration is hindered by high costs. Understanding the target population's expectations and willingness to pay (WTP) for these drugs is crucial. WTP, a key concept in behavioral science, reflects the maximum price consumers are willing to pay for a product, aiding in healthcare cost-effectiveness evaluations. Despite its relevance, only one WTP study has been conducted in the Indian context for diabetes. This study explores WTP for two novel drugs: oral semaglutide and icodec (weekly insulin). Material and methods This observational study, conducted in a diabetes specialty clinic and telemedicine facility in All India Institute of Medical Sciences, Bhopal, India, involved adults (18-80 years) diagnosed with T2DM. Data collection adhered to ethical guidelines, and participants provided written informed consent. Face-to-face interviews were employed to gather socio-economic, demographic, and medical details. Participants estimated their WTP for oral semaglutide and weekly insulin, considering reference ranges for existing antidiabetic treatments. Statistical analyses, including t-tests and analysis of variance, explored sociodemographic and clinical factors influencing WTP. Results Of 105 approached patients, 87 (74.3%) participated. The majority were males (55.2%) with an average age of 57.2 years. The average WTP for oral semaglutide was INR 9.35±5.66 per pill, significantly lower than its market price (INR 315). For weekly insulin (icodec), the WTP was INR 157.25±112.60 per dose. Subgroup analyses revealed no significant correlations based on sociodemographic or clinical parameters. Conclusion This study demonstrated the feasibility of WTP assessments in an Indian outpatient setting, revealing a substantial cost disparity between patients' WTP for oral semaglutide and its market price. The findings underscore the importance of considering WTP in introducing new diabetes medications in India, offering valuable insights for healthcare decision-makers and developers.

Disease-modifying therapies for sickle cell disease: Decisional needs and supports among adolescents and young adults.

BACKGROUND: Shared decision-making is one promising solution to addressing barriers in use of disease-modifying therapies for adolescents and young adults (AYAs) with sickle cell disease (SCD). A thorough understanding of decisional needs can guide the development of decisional supports and promote shared decision-making. PROCEDURE: Informed by the Ottawa Decision Support Framework (ODSF), we conducted a qualitative analysis to assess decisional needs and supports reported by AYAs with SCD, their caregivers, and healthcare providers. Semi-structured qualitative interviews were conducted with AYAs and their caregivers, and online crowdsourcing was used with SCD providers. Thematic and descriptive content analyses were used to summarize perspectives on decisional needs and supports regarding disease-modifying therapies. RESULTS: Fourteen AYAs (Mage  = 21 years, 57% male, 93% non-Hispanic Black, 79% HbSS), 11 caregivers (80% female, 100% non-Hispanic Black), and 40 healthcare providers (65% female, 65% non-Hispanic White, Myears in practice  = 14.8 years, 75% physicians) participated. Thematic analysis revealed needs related to: decisional conflict, inadequate knowledge, unclear expectations, and inadequate supports and resources. Six forms of support emerged as important for decision-making: establishing an open and trusting patient/family-provider relationship, providing information, accepting ambivalence and unreadiness, supporting implementation of a decision, addressing inadequate health and social services, and promoting adequate social, emotional, and instrumental help. CONCLUSIONS: This is the first study to assess decisional needs and supports for AYAs with SCD considering disease-modifying therapies. Additional research is needed to examine which decision supports are the most impactful to promote effective shared decision-making in this population.

Selecting an optimal approach to reduce energy crises under interval-valued intuitionistic fuzzy environment.

The concept of interval-valued intuitionistic fuzzy sets is intellectually stimulating and holds significant utility in the representation and analysis of real-world problems. The development of similarity measures within the class of interval-valued intuitionistic fuzzy sets possesses significant importance across various academic disciplines, particularly in the fields of decision-making and pattern recognition. The utilization of similarity measures is of utmost importance in the decision-making process when implementing interval-valued intuitionistic fuzzy sets. This is due to its inherent capability to quantitatively assess the level of resemblance or similarity between two interval-valued intuitionistic fuzzy sets. In this article, the drawbacks of the existing similarity measures in the context of an interval-valued intuitionistic fuzzy environment are addressed, and a novel similarity measure is presented. Many fundamental properties of this new interval-valued intuitionistic fuzzy similarity measure are also established, and the effectiveness of this similarity measure is illustrated by presenting a useful example. Moreover, a comparison is given to demonstrate the validity of the newly proposed similarity measure within the existing knowledge of similarity measures in the interval-valued intuitionistic fuzzy environment. In addition, an algorithm is designed to solve multi-criteria decision making problems by means of the proposed measure in the interval-valued intuitionistic fuzzy setting. Furthermore, this newly defined similarity measure is successfully applied to select an optimal renewable energy source to reduce energy crises. Finally, we conduct a comparative study to showcase the authenticity of the recently defined technique within the existing knowledge of similarity measures in the interval-valued intuitionistic fuzzy environment.

"Like not having an arm": a qualitative study of the impact of visitor restrictions on cancer care during the COVID-19 pandemic.

PURPOSE: Visitor restriction policies to prevent the spread of COVID-19 among patients and clinicians were widespread during the pandemic, resulting in the exclusion of caregivers at key points of cancer care and treatment decision-making. The aim of this study was to explore how visitor restrictions impacted cancer treatment decision-making and care from patient and physician perspectives. METHODS: Sixty-seven interviews, including 48 cancer patients and 19 cancer and palliative care physicians from four academic cancer centers in the USA between August 2020 and July 2021. RESULTS: Visitor restrictions that prevented caregivers from participating in clinic appointments and perioperative hospital care created challenges in cancer care that spanned three domains: practical, social, and informational. We identified eight themes that characterized challenges within the three domains across all three groups, and that these challenges had negative emotional and psychological consequences for both groups. Physicians perceived that patients' negative experiences due to lack of support through the physical presence of caregivers may have worsened patient outcomes. CONCLUSIONS: Our data demonstrate the tripartite structure of the therapeutic relationship in cancer care with caregivers providing critical support in the decision-making and care process to both patients and physicians. Caregiver absences led to practical, psychosocial, and informational burdens on both groups, and likely increased the risk of burnout among physicians. Our findings suggest that the quality of cancer care can be enhanced by engaging caregivers and promoting their physical presence during clinical encounters.

A novel IFN-CSM-CoCoSo approach for multiple-attribute group decision-making with intuitionistic fuzzy sets: An application in assessing corporate social responsibility performance.

With the rapid growth of the economy, enterprises have encountered a series of problems while pursuing economic benefits, such as food safety and environmental pollution issues, resource shortages and energy consumption issues, which affect the sustainable development of enterprises. Establishing a corporate performance evaluation system from the perspective of social responsibility, based on stakeholder theory and the importance of overall goals reflected in the weight of social responsibility indicators, is a very effective measure to achieve corporate social responsibility (CSR) goals through CSR motivation and stakeholders. The performance evaluation of CSR from the perspective of environmental accounting is a MAGDM. Recently, the CoCoSo technique and cosine similarity measure (CSM) technique was utilized to conduct the MAGDM. The intuitionistic fuzzy sets (IFSs) are utilized as a technique for conducting uncertain information during the performance evaluation of CSR from the perspective of environmental accounting. In this study, the intuitionistic fuzzy CoCoSo based on the CSM (IFN-CSM-CoCoSo) technique is built for MAGDM with IFSs. Finally, a numerical example for performance evaluation of CSR from the perspective of environmental accounting is conducted to verify the IFN-CSM-CoCoSo technique.

Some distance measures for pythagorean cubic fuzzy sets: Application selection in optimal treatment for depression and anxiety.

Pythagorean cubic fuzzy sets represent an advancement beyond conventional interval-valued Pythagorean sets, integrating the principles of Pythagorean fuzzy sets and interval-valued Pythagorean fuzzy sets. Given the critical significance of distance measures in real-world decision-making and pattern recognition tasks, it is noteworthy that there exists a notable gap in the literature regarding distance measures specifically tailored for Pythagorean cubic fuzzy sets. The objectives of this paper are:•To define novel generalized distance measures between Pythagorean cubic fuzzy sets (PCFSs) to tackle intricate decision-making challenges.•These novel distance measures are undergoing testing on a real-world scenario concerning the management of anxiety and depression to evaluate their effectiveness and practical application.•We have illustrated the boundedness and nonlinear characteristics inherent in these distance measures. In addition, we conduct comparative analyses with existing approaches to validate the proposed methodology, thereby providing insights into its advantages and potential applications.

Subjective Rationalities of Nonadherence to Treatment and Vaccination in Healthcare Decision-Making.

Objective: In this short report contributing to the literature on treatment and vaccination adherence, nonadherence was examined from the perspective of decision-making (DM) practice in healthcare. The objective of this study was to survey the rationalities given for treatment nonadherence and their association with DM practice. Methods: The Ottawa decision Support Framework was used as a theoretical background for the study. Multiple choice and open-text responses indicating nonadherence were drawn from vignette survey data. The results have been analyzed and reported as descriptive statistics and findings of data-driven content analysis. The number of observatory units was 1032 in the within-subject study design. Results: DM practice was predominantly associated with nonadherence to vaccination, whereas nonadherence to treatment was consistently associated with attitudinal reasons independent of DM practice. Nonadherence to vaccination was most often rationalized by prior negative experiences in simple DM scenarios. After other DM practices, nonadherence was rationalized by uncertainty and criticism about the benefits of the recommended vaccine. Mistrust toward healthcare providers stood out, first in treatment nonadherence generally and, second, in vaccination nonadherence after simple DM where the final decision was left to the patient. Conclusion: In medical DM, adherence to treatment and vaccination may be achieved through a recognition of patients' previous healthcare encounters and potential trust-related concerns, which could pose a risk for nonadherence. To be able to observe these risks, patient engagement and mutual trust should be priorities in decision support in healthcare.

Research on treatment and vaccination adherence aim at increasing knowledge about improving adherence and treatment outcomes. This study examined explanations given for not adhering to treatment and an association between the explanations and medical decision-making practices. Decision-making practices are known to impact patient­physician interaction and the patients' motivation to have an active role at the appointment. In a shared decision-making (SDM) practice, patients' participation is encouraged. SDM is built on both medical expertise of the practitioner and individual views, values and preferences of the patient. As opposed to SDM, authoritarian decision-making refers to a practice in which decisions are made solely by the physician. In guided decision-making, the physician shares information with the patient but makes the final decision. In simple decision-making, the final decision is left to the patient after consultation. This empirical study used illustrated vignette survey data from Finland. Out of the 1935 respondents, 64% were female with an average age of 68. In the study design, nonadherence was presumed to depend on a decision-making practice presented. Primary findings showed that nonadherence to treatment is most correlated with attitudinal predetermination of the patient and mistrust toward healthcare providers. Nonadherence to vaccination had a stronger association with decision-making practices. After simple decision-making, declining vaccination was most often explained by prior negative experiences and mistrust toward healthcare providers. After other decision-making practices, explanations for declining included uncertainty and criticism about the benefits of the recommended vaccine. This study underscores the pivotal role of trust in the patient-physician interaction.

Acute stress differentially alters reward-related decision making and inhibitory control under threat of punishment.

Acute stress has various effects on cognition, executive function and certain forms of cost/benefit decision making. Recent studies in rodents indicate that acute stress differentially alters reward-related decisions involving particular types of costs and slows choice latencies. Yet, how stress alters decisions where rewards are linked to punishment is less clear. We examined how 1 h restraint stress, followed by behavioral testing 10 min later altered action-selection on two tasks involving reward-seeking under threat of punishment in well-trained male and female rats. One study used a risky decision-making task involving choice between a small/safe reward and a large/risky one that could coincide with shock, delivered with a probability that increased over blocks of trials. Stress increased risk aversion and punishment sensitivity, reducing preference for the larger/risky reward, while increasing decision latencies and trial omissions in both sexes, when rats were teste. A second study used a "behavioral control" task, requiring inhibition of approach towards a readily available reward associated with punishment. Here, food pellets were delivered over discrete trials, half of which coincided with a 12 s audiovisual cue, signalling that reward retrieval prior to cue termination would deliver shock. Stress exerted sex- and timing-dependent effects on inhibitory control. Males became more impulsive and received more shocks on the stress test, whereas females were unaffected on the stress test, and were actually less impulsive when tested 24 h later. None of the effects of restraint stress were recapitulated by systemic treatment with physiological doses of corticosterone. These findings suggest acute stress induces qualitatively distinct and sometimes sex-dependent effects on punished reward-seeking that are critically dependent on whether animals must either choose between different actions or withhold them to obtain rewards and avoid punishment.

Family and developmental correlates of adolescent involvement in decision making about screen use.

Objective: Assess how child involvement in making rules about screen time relates to age, child prosocial functioning, and amount of screen use. Methods: NORC's AmeriSpeak Panel was used to recruit a nationally representative sample of parents or guardians of school-aged children (age 5-17) in the United States (n = 2084). Parents completed survey that included measures of screen time, child involvement in rule making about screen use, family functioning, and dimensions of child psychosocial functioning. Results: Across all age categories, most families had some form of rules about the allowable amount of screen-based digital media for uses other than schoolwork: 86% of elementary school-aged children (ages 5 to 10), 81% of middle school-aged children (ages 11-13), and 61% of high school aged children (ages 14-17). Across all age groups, having rules was associated with fewer hours of screen time (elementary school: B = -1.31, 95% CI = -1.80 to -0.81, p < 0.001; middle school: B = -1.40, 95% CI = -2.20 to -0.59, p < 0.001; high school: B = -0.97, 95% CI = -1.68 to -0.27, p = 0.007). Child involvement in making rules was significantly greater for high school students as compared to elementary school students (ß=0.12, p < 0.001), and not associated with high school- or middle-school aged child screen time. Across all age groups, child involvement in making rules was associated with higher levels of prosocial functioning (elementary school: ß=0.07, p < 0.001; middle school: ß=0.19, p = 0.001; high school: ß=0.21, p < 0.001). Conclusions: Child involvement in making rules about screen use may be an opportunity to strengthen developmentally important competencies, as part of a broader autonomy-supportive approach to parenting.

Entrustment Decision Making in the Intensive Care Unit: It's About More Than the Learner.

Background: The provision of graded supervision affording progressive autonomy is fundamental to the progression of a medical learner toward competency for independent practice; the decision of how much supervision versus autonomy to provide a trainee in the execution of clinical care constitutes an entrustment decision. Despite entrustment decision making occurring both daily in practice and summatively at points of matriculation through stages of medical training, the factors influencing entrustment decisions remain poorly understood across clinical contexts. Objective: This study was designed to explore the central research question: How are entrustment decisions made in the medical intensive care unit (ICU)? Methods: This qualitative case study used semistructured interviews with attending pulmonary and critical care physicians in the medical ICU at a major midwestern medical center to explore the entrustment decision-making process as it was enacted in the clinical environment. Results: Five major themes emerged from the data: 1) task, circumstance, and trainee factors contribute to entrustment decision making; 2) ad hoc entrustment decisions are enacted by supervisors with a consideration of the care team as a unit, not only an individual; 3) autonomy does not only arise out of entrustment, but outcomes of prior autonomous actions by the trainee inform the intention to entrust; 4) entrustment decision making includes a social process of back-and-forth akin to negotiation; and 5) entrustment is a learned skill. Conclusion: The process of entrustment decision making in the ICU is more complex than prior frameworks have captured; a model with more complete incorporation of the factors that influence entrustment in the ICU is presented. It is not clear how often ad hoc entrustment decisions in clinical practice are primarily driven by factors pertaining directly to trainee competence, which carries implications in the use of entrustment for assessment.

Exploring Parental Knowledge, Attitudes, and Factors Influencing Decision-Making in Stem Cell Banking: Rising the Future of Medical Treatment.

BACKGROUND AND OBJECTIVES: Stem cell banking (SCB) is a promising area of modern medicine with the potential to yield innovative treatments and cures. To effectively educate parents and implement laws and regulations that address parental concerns and encourage informed decision-making, it is imperative to emphasize parental viewpoints and their consequences for future healthcare. The study aims to establish the Saudi Arabian population's level of understanding regarding SCB and to comprehend the elements influencing parental knowledge, attitudes, and SCB decision-making processes. METHODOLOGY: A cross-sectional study was conducted among the population in the Makkah region of Saudi Arabia. Demographic data, knowledge levels, attitudes, and decision-making variables were gathered from 380 respondents. RESULTS: The study reveals a lack in their comprehension of the objectives and possible uses of SCB, together with the main sources of information on those banks and conveniently available banking choices. It showed varied results regarding attitudes about considering an SCB for their children. In addition, the majority of respondents had not made a consent decision about SCB for their children. It also illuminates the factors that could influence participants' decisions about SCB for their children and shows that a lack of information and understanding is the main obstacle faced by parents regarding SCB. It highlights that participants were generally in favor of learning more about SCB for their children. CONCLUSIONS: This study broadens our understanding of parental decision-making toward SCB and clarifies the elements influencing parents' opinions and worries and offers significant ramifications for lawmakers, medical professionals, and SCB. These implications can be utilized to enhance communication strategies, create instructional programs, and ease the fears of concerned parents.

An inferential spatiotemporal approach for knowledge synthesis to identify trends in public health research.

Background: Decisions follow patterns that are introduced by human perception. Research and development (R&D) are influenced by these patterns. Furthermore, R&D publications can represent repetitive attempts to solve similar, or the same problems. Literature reviews serve as an important tool for identifying these trends, but they are time consuming. The time commitment of a literature review can be reduced by using a sample of research. This will allow an infinite population of research to be generalized. Additionally, spatiotemporal analysis is most appropriate for fields that follow time and geographic trends, such as public health. Also, using research locations to perform this analysis potentially captures the social return of R&D, as knowledge gained. As a result, an inferential spatiotemporal methodological framework is introduced to quickly identify research trends using public health research. This was applied to a childhood Pb exposure case study. Methods: A body of more than 1000 childhood elevated blood lead (Pb) level (EBLL) research articles were used to extract publication years, research locations, and subtopics. These publications were grouped into research locations (i.e., U.S. states where research was conducted; not publication location) and averaged over years published (i.e., 29 years). Binary indicator variables were derived using the subtopics extracted and the periods identified in time trend analyses. Explanatory variables were used to conduct hypothesis testing. Significant variables were used to generalize the population of the annual average EBLL articles written per state. Results: The range of the annual average of EBLL research articles by state was 0-1.7 articles, with a mean of 0.3 articles. Thirty-eight explanatory variables suggested a significant effect on research article production. These included temporal, sociodemographic, education, structure age, environmental, and economic variables. The strongest effect on research production for U.S. states came from the number of structures built before 1950. A predictive model was selected to generalize the population of articles using time-periods 1990-95, environmental subtopic, and structures built before 1950. The locations with the most research production for this topic were California and New York. The locations with the least research production for this topic were Alaska, Hawaii, Nevada, Wyoming, North Dakota, South Dakota, Mississippi, Delaware, and New Hampshire. Conclusion: If the trend for R&D is to make fast decisions, more human bias will be introduced into the decision-making process. Analytical tools that enable researchers to identify trends and ask more questions about their field will mitigate these biases. This hypothesis testing and predictive modeling methodology provide researchers and other decision makers with analytical tools they can use to quickly identify research trends and narrow their field of research. Additionally, this analysis potentially captures the impact of discovered ideas, as a social return spillover, for this topic.

A novel approach toward cyberbullying with intelligent recommendations using deep learning based blockchain solution.

Integrating healthcare into traffic accident prevention through predictive modeling holds immense potential. Decentralized Defense presents a transformative vision for combating cyberbullying, prioritizing user privacy, fostering a safer online environment, and offering valuable insights for both healthcare and predictive modeling applications. As cyberbullying proliferates in social media, a pressing need exists for a robust and innovative solution that ensures user safety in the cyberspace. This paper aims toward introducing the approach of merging Blockchain and Federated Learning (FL), to create a decentralized AI solutions for cyberbullying. It has also used Alloy Language for formal modeling of social connections using specific declarations that are defined by the novel algorithm in the paper on two different datasets on Cyberbullying and are available online. The proposed novel method uses DBN to run established relation tests amongst the features in two phases, the first is LSTM to run tests to develop established features for the DBN layer and second is that these are run on various blocks of information of the blockchain. The performance of our proposed research is compared with the previous research and are evaluated using several metrics on creating the standard benchmarks for real world applications.

That's out! How expert umpires make leg-before-wicket judgements in cricket.

Despite evidence that elite-level cricket umpires are highly accurate in making leg-before-wicket (LBW) judgements, there is limited understanding as to how they make these judgements. In this study, we explored the explicit LBW decision-making expertise of elite-level cricket umpires (N = 10) via 10 individual semi-structured interviews. Using thematic analysis, we aimed to identify the sources of information that umpires incorporate into their decision-making process. Results indicated that umpires engage in intentional pre-delivery information-gathering to guide their expectations, and to set context-specific parameters as to what would constitute an LBW dismissal. Not only do umpires use information about the ball trajectory, but they also use additional information about the condition of the pitch, the action-capabilities and susceptibilities of players, and the unique requirements of different match formats. Umpires reported employing a gaze-anchor strategy when gathering information for each delivery and described the process of this information as initially intuitive, before engaging in deeper post-hoc reasoning. Findings highlight the importance of including contextual information when exploring officials' decisions and may inform future training interventions for cricket umpires.

Outcome prioritization and preferences among older adults with cancer starting chemotherapy in a randomized clinical trial.

INTRODUCTION: Older adults with cancer facing competing treatments must prioritize between various outcomes. This study assessed health outcome prioritization among older adults with cancer starting chemotherapy. METHODS: Secondary analysis of a randomized trial addressing vulnerabilities in older adults with cancer. Patients completed three validated outcome prioritization tools: 1) Health Outcomes Tool: prioritizes outcomes (survival, independence, symptoms) using a visual analog scale; 2) Now vs. Later Tool: rates the importance of quality of life at three times-today versus 1 or 5 years in the future; and 3) Attitude Scale: rates agreement with outcome-related statements. The authors measured the proportion of patients prioritizing various outcomes and evaluated their characteristics. RESULTS: A total of 219 patients (median [range] age 71 [65-88], 68% with metastatic disease) were included. On the Health Outcomes Tool, 60.7% prioritized survival over other outcomes. Having localized disease was associated with choosing survival as top priority. On the Now vs. Later Tool, 50% gave equal importance to current versus future quality of life. On the Attitude Scale, 53.4% disagreed with the statement "the most important thing to me is living as long as I can, no matter what my quality of life is"; and 82.2% agreed with the statement "it is more important to me to maintain my thinking ability than to live as long as possible". CONCLUSION: Although survival was the top priority for most participants, some older individuals with cancer prioritize other outcomes, such as cognition and function. Clinicians should elicit patient-defined priorities and include them in decision-making.

Learning enhances representations of taste-guided decisions in the mouse gustatory insular cortex.

Learning to discriminate overlapping gustatory stimuli that predict distinct outcomes-a feat known as discrimination learning-can mean the difference between ingesting a poison or a nutritive meal. Despite the obvious importance of this process, very little is known about the neural basis of taste discrimination learning. In other sensory modalities, this form of learning can be mediated by either the sharpening of sensory representations or the enhanced ability of "decision-making" circuits to interpret sensory information. Given the dual role of the gustatory insular cortex (GC) in encoding both sensory and decision-related variables, this region represents an ideal site for investigating how neural activity changes as animals learn a novel taste discrimination. Here, we present results from experiments relying on two-photon calcium imaging of GC neural activity in mice performing a taste-guided mixture discrimination task. The task allows for the recording of neural activity before and after learning induced by training mice to discriminate increasingly similar pairs of taste mixtures. Single-neuron and population analyses show a time-varying pattern of activity, with early sensory responses emerging after taste delivery and binary, choice-encoding responses emerging later in the delay before a decision is made. Our results demonstrate that, while both sensory and decision-related information is encoded by GC in the context of a taste mixture discrimination task, learning and improved performance are associated with a specific enhancement of decision-related responses.

General practitioners' risk literacy and real-world prescribing of potentially hazardous drugs: a cross-sectional study.

BACKGROUND: Overuse of medical care is a pervasive problem. Studies using hypothetical scenarios suggest that physicians' risk literacy influences medical decisions; real-world correlations, however, are lacking. We sought to determine the association between physicians' risk literacy and their real-world prescriptions of potentially hazardous drugs, accounting for conflicts of interest and perceptions of benefit-harm ratios in low-value prescribing scenarios. SETTING AND SAMPLE: Cross-sectional study-conducted online between June and October 2023 via field panels of Sermo (Hamburg, Germany)-with a convenience sample of 304 English general practitioners (GPs). METHODS: GPs' survey responses on their treatment-related risk literacy, conflicts of interest and perceptions of the benefit-harm ratio in low-value prescribing scenarios were matched to their UK National Health Service records of prescribing volumes for antibiotics, opioids, gabapentin and benzodiazepines and analysed for differences. RESULTS: 204 GPs (67.1%) worked in practices with ≥6 practising GPs and 226 (76.0%) reported 10-39 years of experience. Compared with GPs demonstrating low risk literacy, GPs with high literacy prescribed fewer opioids (mean (M): 60.60 vs 43.88 prescribed volumes/1000 patients/6 months, p=0.016), less gabapentin (M: 23.84 vs 18.34 prescribed volumes/1000 patients/6 months, p=0.023), and fewer benzodiazepines (M: 17.23 vs 13.58 prescribed volumes/1000 patients/6 months, p=0.037), but comparable volumes of antibiotics (M: 48.84 vs 40.61 prescribed volumes/1000 patients/6 months, p=0.076). High-risk literacy was associated with lower conflicts of interest (ϕ = 0.12, p=0.031) and higher perception of harms outweighing benefits in low-value prescribing scenarios (p=0.007). Conflicts of interest and benefit-harm perceptions were not independently associated with prescribing behaviour (all ps >0.05). CONCLUSIONS AND RELEVANCE: The observed association between GPs with higher risk literacy and the prescription of fewer hazardous drugs suggests the importance of risk literacy in enhancing patient safety and quality of care.