Health care is at a turning point. We are shifting from protocolized medicine to precision medicine, and digital health systems are facilitating this shift. By providing clinicians with detailed information for each patient and analytic support for decision-making at the point of care, digital health technologies are enabling a new era of precision medicine. Genomic data also provide clinicians with information that can improve the accuracy and timeliness of diagnosis, optimize prescribing, and target risk reduction strategies, all of which are key elements for precision medicine. However, genomic data are predominantly seen as diagnostic information and are not routinely integrated into the clinical workflows of electronic medical records. The use of genomic data holds significant potential for precision medicine; however, as genomic data are fundamentally different from the information collected during routine practice, special considerations are needed to use this information in a digital health setting. This paper outlines the potential of genomic data integration with electronic records, and how these data can enable precision medicine.

BACKGROUND: Femoral neck fracture (FNF) accounts for approximately 3.58% of all fractures in the entire body, exhibiting an increasing trend each year. According to a survey, in 1990, the total number of hip fractures in men and women worldwide was approximately 338,000 and 917,000, respectively. In China, FNFs account for 48.22% of hip fractures. Currently, many studies have been conducted on postdischarge mortality and mortality risk in patients with FNF. However, there have been no definitive studies on in-hospital mortality or its influencing factors in patients with severe FNF admitted to the intensive care unit.
OBJECTIVE: In this paper, 3 machine learning methods were used to construct a nosocomial death prediction model for patients admitted to intensive care units to assist clinicians in early clinical decision-making.
METHODS: A retrospective analysis was conducted using information of a patient with FNF from the Medical Information Mart for Intensive Care III. After balancing the data set using the Synthetic Minority Oversampling Technique algorithm, patients were randomly separated into a 70% training set and a 30% testing set for the development and validation, respectively, of the prediction model. Random forest, extreme gradient boosting, and backpropagation neural network prediction models were constructed with nosocomial death as the outcome. Model performance was assessed using the area under the receiver operating characteristic curve, accuracy, precision, sensitivity, and specificity. The predictive value of the models was verified in comparison to the traditional logistic model.
RESULTS: A total of 366 patients with FNFs were selected, including 48 cases (13.1%) of in-hospital death. Data from 636 patients were obtained by balancing the data set with the in-hospital death group to survival group as 1:1. The 3 machine learning models exhibited high predictive accuracy, and the area under the receiver operating characteristic curve of the random forest, extreme gradient boosting, and backpropagation neural network were 0.98, 0.97, and 0.95, respectively, all with higher predictive performance than the traditional logistic regression model. Ranking the importance of the feature variables, the top 10 feature variables that were meaningful for predicting the risk of in-hospital death of patients were the Simplified Acute Physiology Score II, lactate, creatinine, gender, vitamin D, calcium, creatine kinase, creatine kinase isoenzyme, white blood cell, and age.
CONCLUSIONS: Death risk assessment models constructed using machine learning have positive significance for predicting the in-hospital mortality of patients with severe disease and provide a valid basis for reducing in-hospital mortality and improving patient prognosis.

UNASSIGNED: The basic product information, health, safety, and nutritional details, as well as food marketing, advertising, and promotion, are all provided on a packed food label. This study was carried out to assess the knowledge, attitude, and practices of the shoppers regarding food labels as there are few studies done in India and none in Pune.
UNASSIGNED: A cross-sectional study was carried out among 226 participants using a validated semi-structured questionnaire, which consisted of sociodemographic details and questions on their knowledge, attitude, and practice regarding food labels while purchasing a packed food item. Quantitative data are presented in the form of mean, standard deviation, 95% confidence interval (CI) of mean, median, and interquartile range (IQR). Qualitative data are in terms of number (N), percentages (%), and 95% CI of percentage.
UNASSIGNED: Of the 226 participants, 163 (72.12) were aware of the label on packaged foods. One hundred seventy-seven (78.32%) participants in all read the label on the packaged food. The maximum retail price (MRP) and expiration date were the most frequent labels sought. Although 17.7% of consumers did not consider nutrient composition when making a purchase, energy and protein were the most often considered nutrients. The majority (70.35%) falsely believed that juice was healthy. The packed food label\'s tiny font made it difficult to read for 30.38% of the customers.
UNASSIGNED: Despite the increased awareness about packed food labeling, a fraction of shoppers were not concerned about nutritional information. In contrast to the prevailing knowledge, the majority believes packed food has a positive effect on health.

Many everyday decisions, including those concerning our health, finances and the environment, involve choosing between a smaller but imminent reward (e.g., €20 now) and a later but larger reward (e.g., €40 in a month). The extent to which an individual prefers smaller imminent rewards over larger delayed rewards can be measured using delay discounting tasks. Acute stress induces a cascade of biological and psychological responses with potential consequences for how individuals think about the future, process rewards, and make decisions, all of which can impact delay discounting. Several studies have shown that individuals focus more on imminent rewards under stress. These findings have been used to explain why individuals make detrimental choices under acute stress. Yet, the evidence linking acute stress to delay discounting is equivocal. To address this uncertainty, we conducted a meta-analysis of 11 studies (14 effects) to systematically quantify the effects of acute stress on monetary delay discounting. Overall, we find no effect of acute stress on delay discounting, compared to control conditions (SMD = -0.18, 95% CI [-0.57, 0.20], p = 0.32). We also find that neither the gender/sex of the participants, the type of stressor (e.g., physical vs. psychosocial) nor whether monetary decisions were hypothetical or incentivized (i.e. monetary decisions were actually paid out) moderated the impact of acute stress on monetary delay discounting. We argue that establishing the effects of acute stress on the separate processes involved in delay discounting, such as reward valuation and prospection, will help to resolve the inconsistencies in the field.

S/S carriers of 5-HTTLPR have been found to be more risk seeking for losses compared to L/L carriers. This finding may be the result of reduced top-down control from the frontal cortex due to altered signal pathways involving the amygdala and ventral striatum. The serotonergic system is known to be involved in neurodevelopment and neuroplasticity. Therefore, the aim of this study was to investigate whether structural differences in white matter can explain the differences in risk-seeking behaviour. Lower structural connectivity in S/S compared to L/L carriers and a negative relationship between risk seeking for losses and connectivity were assumed. Diffusion-weighted imaging was used to compute diffusion parameters for the frontostriatal and uncinate tract in 175 genotyped individuals. The results showed no significant relationship between diffusion parameters and risk seeking for losses. Furthermore, we did not find significant differences in diffusion parameters of the S/S vs. L/L group. There were only group differences in the frontostriatal tract showing stronger structural connectivity in the S/L group, which is also reflected in the whole brain approach. Therefore, the data do not support the hypothesis that the association between 5-HTTLPR and risk seeking for losses is related to differences in white matter pathways implicated in decision-making.

BACKGROUND: How healthcare professionals understand and use concepts of social and cognitive capabilities will influence their behaviour and their understanding of others\' behaviour. Differing understandings of concepts might lead to healthcare professionals not acting in accordance with other healthcare professionals\' expectations. Therefore, part of the problem concerning errors and adverse incidents concerning social and cognitive capabilities might be due to varying understandings of concepts among different healthcare professionals. This study aimed to examine the variations in how educators at the Copenhagen Academy for Medical Education and Simulation talk about social and cognitive capabilities.
METHODS: The study was conducted using semi-structured interviews and directed content analysis. The codes for the analysis process were derived from existing non-technical skills models and used to show variations in how the participants talk about the same concepts.
RESULTS: Educators with a background as nurses and physicians, talked differently about leadership and decision-making, with the nurses paying greater attention to group dynamics and external factors when describing both leadership and decision-making, whereas physicians focus on their individual efforts.
CONCLUSIONS: We found patterned differences in how the participants described leadership and decision-making that may be related to participants\' professional training/background. As it can create misunderstandings and unsafe situations if nurses and physicians disagree on the meaning of leadership and decision-making (without necessarily recognising this difference), it could be beneficial to educate healthcare professionals to be aware of the specificity of their own concepts, and to communicate what exactly they mean by using a particular concept, e.g. \"I want you to coordinate tasks\" instead of \"I want better leadership\".

BACKGROUND: Nigeria commenced rollout of vaccination for coronavirus disease 2019 (COVID-19) in March 2021 as part of the national public health response to the pandemic. Findings from appropriately contextualized cost-effectiveness analyses (CEA) as part of a wider process involving health technology assessment (HTA) approaches have been important in informing decision-making in this area. In this paper we outline the processes that were followed to identify COVID-19 vaccine stakeholders involved in the selection, approval, funding, procurement and rollout of vaccines in Nigeria, and describe the process routes we identified to support uptake of HTA-related information for evidence-informed policy in Nigeria.
METHODS: Our approach to engaging with policy-makers and other stakeholders as part of an HTA of COVID vaccination in Nigeria consisted of three steps, namely: (i) informal discussions with key stakeholders; (ii) stakeholder mapping, analysis and engagement; and (iii) communication and dissemination strategies for the HTA-relevant evidence produced. The analysis of the stakeholder mapping uses the power/interest grid framework.
RESULTS: The informal discussion with key stakeholders generated six initial policy questions. Further discussions with policy-makers yielded three suitable policy questions for analysis: which COVID-19 vaccines should be bought; what is the optimal mode of delivery of these vaccines; and what are the cost and cost-effectiveness of vaccinating people highlighted in Nigeria\'s phase 2 vaccine rollout prioritized by the government, especially the inclusion of those aged between 18 and 49 years. The stakeholder mapping exercise highlighted the range of organizations and groups within Nigeria that could use the information from this HTA to guide decision-making. These stakeholders included both public/government, private and international organizations The dissemination plan developed included disseminating the full HTA results to key stakeholders; production of policy briefs; and presentation at different national and international conferences and peer-reviewed publications.
CONCLUSIONS: HTA processes that involve stakeholder engagement will help ensure important policy questions are taken into account when designing any HTA including any underpinning evidence generation. Further guidance about stakeholder engagement throughout HTA is required, especially for those with low interest in vaccine procurement and use.

BACKGROUND: Although male participation in maternal health has gained increasing recognition and support over the years, little is known about male involvement during pregnancy in the Democratic Republic of the Congo. This paper identified male involvement patterns during pregnancy and evaluated their associations with pregnancy and birth preparedness knowledge, gender-equitable attitudes, self-efficacy, and co-parental relationship factors. Lastly, it explored the moderating effect of gender-equitable attitudes and intimate partner violence on the association between relationship satisfaction and male involvement.
METHODS: Data from the 2018 Momentum baseline study were analyzed to determine the predictors of involvement. Factor analysis was used to create male involvement indices for antenatal carebirth preparedness and shared decision making. The sample consisted of 1,674 male partners of nulliparous pregnant women who were 6 months pregnant at baseline.
RESULTS: Male involvement in individual pregnancy-related activities was low, ranging from 11% (finding a blood donor) to 49% (saving money during emergencies). Knowledge of the number of antenatal care visits, birth preparedness steps, and newborn danger signs were positively associated with involvement in antenatal care/birth preparedness activities while knowledge of antenatal care benefits was positively associated with involvement in shared decisions. Increasing relationship satisfaction and self-efficacy were associated with antenatal care/birth preparedness involvement and for shared decisions, a positive association with gender-equitable attitude and a negative association with self-efficacy were observed. Moderation effects were also detected.
CONCLUSIONS: The findings suggest that male involvement is multifaceted and factors influencing involvement vary depending on the type of involvement. Addressing these factors can improve male participation in maternal health.

Reaction time (RT) is a widely used measure for testing physical performance in motor tasks. This study focused on assessing the processing speed in athletes. Twenty-five healthy volunteers were assigned to the control (n = 16) or athletes groups (n = 9). They were evaluated during motor reaction tasks based on visual stimuli and three difficulty conditions. Physiological measures were obtained from motion capture and electromyography recordings of several muscles. Two RT phases, decision-making (DMK) and electromechanical delay (EMD), were used to analyze the processing speed. The results show significant RT differences between groups. The athletes were ~30% faster compared to the control group. Despite the fact that all participants were right-handed, RT did not show any differences between hands performances in any group. However, DMK time revealed significant differences between the hands. Controls showed a longer DMK time for the right-hand election, ~20% more than the left, while athletes showed no such disparity. These findings reveal that quantifying the decision-making component of reaction time is crucial to assessing processing speed in sport. This approach could facilitate the monitoring of adaptations in both motor-cognitive and neuromuscular processes. The theoretical implications presented in this study offer perspectives on handedness research.

Human decision-making is increasingly supported by artificial intelligence (AI) systems. From medical imaging analysis to self-driving vehicles, AI systems are becoming organically embedded in a host of different technologies. However, incorporating such advice into decision-making entails a human rationalization of AI outputs for supporting beneficial outcomes. Recent research suggests intermediate judgments in the first stage of a decision process can interfere with decisions in subsequent stages. For this reason, we extend this research to AI-supported decision-making to investigate how intermediate judgments on AI-provided advice may influence subsequent decisions. In an online experiment (N = 192), we found a consistent bolstering effect in trust for those who made intermediate judgments and over those who did not. Furthermore, violations of total probability were observed at all timing intervals throughout the study. We further analyzed the results by demonstrating how quantum probability theory can model these types of behaviors in human-AI decision-making and ameliorate the understanding of the interaction dynamics at the confluence of human factors and information features.