How is bioelectrical impedance used in neonatal intensive care? A scoping review.

Poor growth and nutrition management in the neonatal period can have a negative impact upon both the short- and long-term outcomes for the infant. Improvements in bioelectrical impedance technology and accompanying licencing agreements now make this enhanced device available for use in infants as small as 23 weeks gestational age. An exploration of this technology and its use is now timely. The aim of the scoping review was to answer the following question: in preterm and sick term infants in the neonatal intensive care unit, how is bioelectrical impedance being utilized, in what situations, and when? The scoping review was conducted using Arksey and O'Malley's (Int J Soc Res Methodol 8(1):19-32, 2005) framework. Forty-nine papers were initially identified and 16 were included in the scoping review. Three studies were experimental designs, and 13 were observational studies. The review found that BIA was used in neonatal intensive care in three main ways, for, (1) fluid status evaluation, (2) as a measure of adequate nutrition and growth, (3) to validate the technology as an outcome measure in neonates. CONCLUSION: There is a paucity of recent robust research papers which investigate the use of bioelectrical impedance in preterm neonates. Available evidence spans a range of 30 years, with technological advancement reducing the application of older studies to the modern neonatal setting. Although this technology may be helpful for decision-making around fluid management and nutrition, in preterm infants, robust evidence is needed to demonstrate the clinical benefit of bioelectrical impedance beyond that of usual care. WHAT IS KNOWN: • Clinical decisions regarding neonatal nutrition and fluid management are currently based upon the interpretation of vital signs, fluid balance, weight trend, biochemical markers, and physical examination. • Bioelectrical Impedance Analysis (BIA) is a non-invasive method of assessing body composition which is now available to be used in infants as small as 23 weeks gestation. WHAT IS NEW: • Bioelectrical Impedance has been used in three main ways in the NICU, for fluid status evaluation, for measuring nutrition and growth and to validate BIA as an outcome. • There is a lack of recent robust research data to support the use of the device within clinical decision making in neonatal intensive care.

Differences in discharge letter content: oncologists' vs. home care physicians' needs.

PURPOSE: To compare the details, oncologists include in discharge letters with what home care physicians need. Although discharge letters are important to share patients' information for home palliative care, few studies have compared the details, especially patients' emotions, regarding what oncologists include in discharge letters and home care physicians' needs. METHODS: This cross-sectional study was conducted by sending anonymous, self-administered questionnaires to 500 certified oncologists (OCs) and 500 directors of home care supporting clinics (HCs) in Japan between March and May 2023. The survey considered 20 potential items found in discharge letters, and compared rates of OCs including these items and HCs needs. RESULTS: Of 310 valid responses, 186 were from OCs (average age: 47.7; 29 females) and 124 from HCs (average age: 55.4; 9 females). Major items with lower inclusion rates for OCs included patients' emotions regarding medical conditions (58.4% in OCs vs. 92.6% in HCs, p < 0.001), families' emotions regarding medical conditions (60.0 vs. 92.6%, respectively, p < 0.001), patients' perceptions regarding medical conditions (84.9 vs. 94.3%, respectively, p = 0.011), families' perceptions regarding medical conditions (84.3 vs. 95.1%, respectively, p = 0.004), and potential late-onset treatment-related adverse events (79.3 vs. 92.6%, respectively, p = 0.002). Conversely, OCs included patients' activities of daily living more frequently (96.2 vs. 90.2%, respectively, p = 0.031). CONCLUSION: Transitioning to home-based palliative care may necessitate accurate information and consideration of patients' and families' perceptions and emotions regarding medical conditions in discharge letters for continuous provision of high-quality care.

Maintaining essential health services during a pandemic: lessons from Costa Rica's COVID-19 response.

Studies on COVID-19 usually focus on health system responses to decrease the rate of COVID-19 infection and death, but patients with other diseases also require access to health services during the pandemic. This paper describes the structures and processes by which the Costa Rican Social Security Fund (CCSS) changed in response to the COVID-19 pandemic, which helped to sustain essential health services (EHSs). We conducted a desk review of the local literature and semistructured qualitative interviews with key informants from the CCSS. We found that the CCSS implemented changes in structure, such as creating a specialised COVID-19 centre and hiring additional interim health workers. The CCSS also implemented changes in processes, including leveraging its integrated network to optimise its resources and support alternative care modalities. These changes generated changes in outputs and outcomes that helped sustain EHSs for non-COVID-19 patients. These interventions were possible primarily due to Costa Rica's underlying health system, particularly its integrated nature with a single institution in charge of healthcare provision financed through mandatory health insurance, a unique digital medical record system and a contingency fund.

Developmental differences in children and adults' enforcement of explore versus exploit search strategies in the United States and Turkey.

Across development, as children acquire a deeper understanding of their environment, they explore less and take advantage, or "exploit," what they already know. Here, we test whether children also enforce exploration-oriented search behaviors onto others. Specifically, we ask whether children are more likely to encourage a search agent to explore versus exploit their environment, and whether this pattern varies across childhood (between 3 and 6 years). We also ask whether this pattern differs between children and adults, and generalizes across two different sociocultural contexts-Turkey and the United States-that differ on dimensions that might relate to children's decisions about exploration (e.g., curiosity-focused educational practices, attitudes toward uncertainty avoidance). Participants (N = 358) watched an agent search for rewards and were asked at various points whether the agent should "stay" (exploit) in their current location, or "go" (explore) to a new location. At all points in the experiment, children enforced exploration significantly more often than adults. Early in the agent's search, children in the US enforced exploration more often than children in Turkey; later in the search, younger children (from both sociocultural contexts) were more likely to continue enforcing exploration compared to older children. These findings highlight that children are not only highly exploratory themselves, but also enforce exploration onto others-underscoring the central role that exploration plays in driving early cognitive development across diverse sociocultural contexts. RESEARCH HIGHLIGHTS: The current study examined developmental and cross-cultural differences in children and adults' enforcement of explore-exploit search strategies. Children in the US and Turkey enforced exploration more than adults, who enforced exploitation more often; results were generally consistent across cultures with small differences. Mirroring developmental changes in children's own search behavior; the tendency to enforce exploration decreased between 3- to 6-years of age. Findings underscore the central role of an "exploration mindset" in children's early decision-making-even when exploration has no direct benefits to the child themselves.

A qualitative evaluation of factors influencing Tumor Treating fields (TTFields) therapy decision making among brain tumor patients and physicians.

BACKGROUND: Tumor Treating Fields (TTFields) Therapy is an FDA-approved therapy in the first line and recurrent setting for glioblastoma. Despite Phase 3 evidence showing improved survival with TTFields, it is not uniformly utilized. We aimed to examine patient and clinician views of TTFields and factors shaping utilization of TTFields through a unique research partnership with medical neuro oncology and medical social sciences. METHODS: Adult glioblastoma patients who were offered TTFields at a tertiary care academic hospital were invited to participate in a semi-structured interview about their decision to use or not use TTFields. Clinicians who prescribe TTFields were invited to participate in a semi-structured interview about TTFields. RESULTS: Interviews were completed with 40 patients with a mean age of 53 years; 92.5% were white and 60% were male. Participants who decided against TTFields stated that head shaving, appearing sick, and inconvenience of wearing/carrying the device most influenced their decision. The most influential factors for use of TTFields were the efficacy of the device and their clinician's opinion. Clinicians (N = 9) stated that TTFields was a good option for glioblastoma patients, but some noted that their patients should consider the burdens and benefits of TTFields as it may not be the desired choice for all patients. CONCLUSIONS: This is the first study to examine patient decision making for TTFields. Findings suggest that clinician support and efficacy data are among the key decision-making factors. Properly understanding the path to patients' decision making is crucial in optimizing the use of TTFields and other therapeutic decisions for glioblastoma patients.

From algorithms to action: improving patient care requires causality.

In cancer research there is much interest in building and validating outcome prediction models to support treatment decisions. However, because most outcome prediction models are developed and validated without regard to the causal aspects of treatment decision making, many published outcome prediction models may cause harm when used for decision making, despite being found accurate in validation studies. Guidelines on prediction model validation and the checklist for risk model endorsement by the American Joint Committee on Cancer do not protect against prediction models that are accurate during development and validation but harmful when used for decision making. We explain why this is the case and how to build and validate models that are useful for decision making.

Bayesian Reinforcement Learning With Limited Cognitive Load.

All biological and artificial agents must act given limits on their ability to acquire and process information. As such, a general theory of adaptive behavior should be able to account for the complex interactions between an agent's learning history, decisions, and capacity constraints. Recent work in computer science has begun to clarify the principles that shape these dynamics by bridging ideas from reinforcement learning, Bayesian decision-making, and rate-distortion theory. This body of work provides an account of capacity-limited Bayesian reinforcement learning, a unifying normative framework for modeling the effect of processing constraints on learning and action selection. Here, we provide an accessible review of recent algorithms and theoretical results in this setting, paying special attention to how these ideas can be applied to studying questions in the cognitive and behavioral sciences.

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.

Do incidental positive emotions induce more optimistic expectations of decision outcomes? An empirical study from the perspective of event-related potential.

INTRODUCTION: Previous research has found that incidental emotions of different valences (positive/negative/neutral) influence risky decision-making. However, the mechanism of their influence on psychological expectations of decision outcomes remains unclear. METHODS: We explored the effects of different incidental emotions on the behavioral, psychological, and electrophysiological responses of individuals in risky decision-making through a money gambling task using a one-way (emotion type: positive, negative, neutral emotions) between-subjects experimental design. RESULTS: Individuals with positive emotions had significantly greater risk-seeking rates than those with negative emotions during the decision selection phase (p < .01). In the feedback stage of decision outcomes, individuals showed stronger perceptions of uncertainty in the decision environment under gain and loss feedback compared with neutral feedback, as evidenced by a more positive P2 component (i.e., the second positive component of an event-related potential). Positive emotions produced greater than expected outcome bias than neutral emotions, as evidenced by a more negative FRN component (i.e., the feedback-related negativity component). CONCLUSION: Our results suggest that positive emotions increase individuals' psychological expectations of decision outcomes. This study provides new empirical insights to understand the influence of incidental emotions on risky decision outcome expectations.

Development of a scoring system to quantify errors from semantic characteristics in incident reports.

OBJECTIVES: Incident reporting systems are widely used to identify risks and enable organisational learning. Free-text descriptions contain important information about factors associated with incidents. This study aimed to develop error scores by extracting information about the presence of error factors in incidents using an original decision-making model that partly relies on natural language processing techniques. METHODS: We retrospectively analysed free-text data from reports of incidents between January 2012 and December 2022 from Nagoya University Hospital, Japan. The sample data were randomly allocated to equal-sized training and validation datasets. We conducted morphological analysis on free text to segment terms from sentences in the training dataset. We calculated error scores for terms, individual reports and reports from staff groups according to report volume size and compared these with conventional classifications by patient safety experts. We also calculated accuracy, recall, precision and F-score values from the proposed 'report error score'. RESULTS: Overall, 114 013 reports were included. We calculated 36 131 'term error scores' from the 57 006 reports in the training dataset. There was a significant difference in error scores between reports of incidents categorised by experts as arising from errors (p<0.001, d=0.73 (large)) and other incidents. The accuracy, recall, precision and F-score values were 0.8, 0.82, 0.85 and 0.84, respectively. Group error scores were positively associated with expert ratings (correlation coefficient, 0.66; 95% CI 0.54 to 0.75, p<0.001) for all departments. CONCLUSION: Our error scoring system could provide insights to improve patient safety using aggregated incident report data.

Impact of an ICU bed capacity optimisation method on the average length of stay and average cost of hospitalisation following implementation of China's open policy with respect to COVID-19: a difference-in-differences analysis based on information management system data from a tertiary hospital in southwest China.

OBJECTIVES: Following the implementation of China's open policy with respect to COVID-19 on 7 December 2022, the influx of patients with infectious diseases has surged rapidly, necessitating hospitals to adopt temporary requisition and modification of ward beds to optimise hospital bed capacity and alleviate the burden of overcrowded patients. This study aims to investigate the effect of an intensive care unit (ICU) bed capacity optimisation method on the average length of stay (ALS) and average cost of hospitalisation (ACH) after the open policy of COVID-19 in China. DESIGN AND SETTING: A difference-in-differences (DID) approach is employed to analyse and compare the ALS and ACH of patients in four modified ICUs and eight non-modified ICUs within a tertiary hospital located in southwest China. The analysis spans 2 months before and after the open policy, specifically from 5 October 2022 to 6 December 2022, and 7 December 2022 to 6 February 2023. PARTICIPANTS: We used the daily data extracted from the hospital's information management system for a total of 5944 patients admitted by the outpatient and emergency access during the 2-month periods before and after the release of the open policy in China. RESULTS: The findings indicate that the ICU bed optimisation method implemented by the tertiary hospital led to a significant reduction in ALS (HR -0.6764, 95% CI -1.0328 to -0.3201, p=0.000) and ACH (HR -0.2336, 95% CI -0.4741 to -0.0068, p=0.057) among ICU patients after implementation of the open policy. These results were robust across various sensitivity analyses. However, the effect of the optimisation method exhibits heterogeneity among patients admitted through the outpatient and emergency channels. CONCLUSIONS: This study corroborates a significant positive impact of ICU bed optimisation in mitigating the shortage of medical resources following an epidemic outbreak. The findings hold theoretical and practical implications for identifying effective emergency coordination strategies in managing hospital bed resources during sudden public health emergency events. These insights contribute to the advancement of resource management practices and the promotion of experiences in dealing with public health emergencies.

Utilisation and impact of predict prostate on decision-making among clinicians and patients in a specialist tertiary referral centre: A retrospective cohort study.

Background: Patients with intermediate-risk prostate cancer are faced with the decision of whether to undergo radical treatment. Decision-making aids, such as Predict Prostate, can empower both clinicians and patients to make treatment decisions with personalised information, but their impact on multi-disciplinary team (MDT) decision-making and uptake of radical treatment remains unknown. Objective: The objective of this study is to assess the utilisation and utility of Predict Prostate in informing treatment decisions for patients with intermediate-risk prostate cancer. Patients and Methods: A retrospective cohort study was conducted in Cambridge University Hospitals (CUH) of patients referred to the prostate cancer specialist multi-disciplinary team (pcSMDT) and robotic prostatectomy clinic (ROPD) between September 2019 and August 2021 for consideration of radical prostatectomy (RARP). Data on patient characteristics, use of PredictProstate and management decisions were collected from the Epic electronic medical record (EMR) of 839 patients, of whom 386 had intermediate-risk prostate cancer. Results: The use of Predict Prostate at the pcSMDT increased in the second half of the study period (34.5% vs. 23.8%, p < 0.001). The use of Predict Prostate was associated with an increased likelihood of attending ROPD for men with CPG2 prostate cancer (OR = 2.155, 95% CI = 1.158-4.013, p = 0.015) but a reduced likelihood of proceeding with RARP for men with CPG2 (OR = 0.397, 95% CI = 0.209-0.753, p = 0.005) and CPG3 (OR = 0.305, 95% CI = 0.108-0.861, p = 0.025) prostate cancer. Conclusion: Our study showed that the use of Predict Prostate for patients with intermediate-risk prostate cancer is associated with increased attendance at specialist surgical clinic and a reduced chance of undergoing radical prostate surgery.

Decision discovery using clinical decision support system decision log data for supporting the nurse decision-making process.

BACKGROUND: Decision-making in healthcare is increasingly complex; notably in hospital environments where the information density is high, e.g., emergency departments, oncology departments, and psychiatry departments. This study aims to discover decisions from logged data to improve the decision-making process. METHODS: The Design Science Research Methodology (DSRM) was chosen to design an artifact (algorithm) for the discovery and visualization of decisions. The DSRM's different activities are explained, from the definition of the problem to the evaluation of the artifact. During the design and development activities, the algorithm itself is created. During the demonstration and evaluation activities, the algorithm was tested with an authentic synthetic dataset. RESULTS: The results show the design and simulation of an algorithm for the discovery and visualization of decisions. A fuzzy classifier algorithm was adapted for (1) discovering decisions from a decision log and (2) visualizing the decisions using the Decision Model and Notation standard. CONCLUSIONS: In this paper, we show that decisions can be discovered from a decision log and visualized for the improvement of the decision-making process of healthcare professionals or to support the periodic evaluation of protocols and guidelines.

Brain activity of professional investors signals future stock performance.

A major aspiration of investors is to better forecast stock performance. Interestingly, emerging "neuroforecasting" research suggests that brain activity associated with anticipatory reward relates to market behavior and population-wide preferences, including stock price dynamics. In this study, we extend these findings to professional investors processing comprehensive real-world information on stock investment options while making predictions of long-term stock performance. Using functional MRI, we sampled investors' neural responses to investment cases and assessed whether these responses relate to future performance on the stock market. We found that our sample of investors could not successfully predict future market performance of the investment cases, confirming that stated preferences do not predict the market. Stock metrics of the investment cases were not predictive of future stock performance either. However, as investors processed case information, nucleus accumbens (NAcc) activity was higher for investment cases that ended up overperforming in the market. These findings remained robust, even when controlling for stock metrics and investors' predictions made in the scanner. Cross-validated prediction analysis indicated that NAcc activity could significantly predict future stock performance out-of-sample above chance. Our findings resonate with recent neuroforecasting studies and suggest that brain activity of professional investors may help in forecasting future stock performance.

Exploring the Use and Implications of AI in Sexual and Reproductive Health and Rights: Protocol for a Scoping Review.

BACKGROUND: Artificial intelligence (AI) has emerged as a transformative force across the health sector and has garnered significant attention within sexual and reproductive health and rights (SRHR) due to polarizing views on its opportunities to advance care and the heightened risks and implications it brings to people's well-being and bodily autonomy. As the fields of AI and SRHR evolve, clarity is needed to bridge our understanding of how AI is being used within this historically politicized health area and raise visibility on the critical issues that can facilitate its responsible and meaningful use. OBJECTIVE: This paper presents the protocol for a scoping review to synthesize empirical studies that focus on the intersection of AI and SRHR. The review aims to identify the characteristics of AI systems and tools applied within SRHR, regarding health domains, intended purpose, target users, AI data life cycle, and evidence on benefits and harms. METHODS: The scoping review follows the standard methodology developed by Arksey and O'Malley. We will search the following electronic databases: MEDLINE (PubMed), Scopus, Web of Science, and CINAHL. Inclusion criteria comprise the use of AI systems and tools in sexual and reproductive health and clear methodology describing either quantitative or qualitative approaches, including program descriptions. Studies will be excluded if they focus entirely on digital interventions that do not explicitly use AI systems and tools, are about robotics or nonhuman subjects, or are commentaries. We will not exclude articles based on geographic location, language, or publication date. The study will present the uses of AI across sexual and reproductive health domains, the intended purpose of the AI system and tools, and maturity within the AI life cycle. Outcome measures will be reported on the effect, accuracy, acceptability, resource use, and feasibility of studies that have deployed and evaluated AI systems and tools. Ethical and legal considerations, as well as findings from qualitative studies, will be synthesized through a narrative thematic analysis. We will use the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) format for the publication of the findings. RESULTS: The database searches resulted in 12,793 records when the searches were conducted in October 2023. Screening is underway, and the analysis is expected to be completed by July 2024. CONCLUSIONS: The findings will provide key insights on usage patterns and evidence on the use of AI in SRHR, as well as convey key ethical, safety, and legal considerations. The outcomes of this scoping review are contributing to a technical brief developed by the World Health Organization and will guide future research and practice in this highly charged area of work. TRIAL REGISTRATION: OSF Registries osf.io/ma4d9; https://osf.io/ma4d9. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/53888.

Usability of an Automated System for Real-Time Monitoring of Shared Decision-Making for Surgery: Mixed Methods Evaluation.

BACKGROUND: Improving shared decision-making (SDM) for patients has become a health policy priority in many countries. Achieving high-quality SDM is particularly important for approximately 313 million surgical treatment decisions patients make globally every year. Large-scale monitoring of surgical patients' experience of SDM in real time is needed to identify the failings of SDM before surgery is performed. We developed a novel approach to automating real-time data collection using an electronic measurement system to address this. Examining usability will facilitate its optimization and wider implementation to inform interventions aimed at improving SDM. OBJECTIVE: This study examined the usability of an electronic real-time measurement system to monitor surgical patients' experience of SDM. We aimed to evaluate the metrics and indicators relevant to system effectiveness, system efficiency, and user satisfaction. METHODS: We performed a mixed methods usability evaluation using multiple participant cohorts. The measurement system was implemented in a large UK hospital to measure patients' experience of SDM electronically before surgery using 2 validated measures (CollaboRATE and SDM-Q-9). Quantitative data (collected between April 1 and December 31, 2021) provided measurement system metrics to assess system effectiveness and efficiency. We included adult patients booked for urgent and elective surgery across 7 specialties and excluded patients without the capacity to consent for medical procedures, those without access to an internet-enabled device, and those undergoing emergency or endoscopic procedures. Additional groups of service users (group 1: public members who had not engaged with the system; group 2: a subset of patients who completed the measurement system) completed user-testing sessions and semistructured interviews to assess system effectiveness and user satisfaction. We conducted quantitative data analysis using descriptive statistics and calculated the task completion rate and survey response rate (system effectiveness) as well as the task completion time, task efficiency, and relative efficiency (system efficiency). Qualitative thematic analysis identified indicators of and barriers to good usability (user satisfaction). RESULTS: A total of 2254 completed surveys were returned to the measurement system. A total of 25 service users (group 1: n=9; group 2: n=16) participated in user-testing sessions and interviews. The task completion rate was high (169/171, 98.8%) and the survey response rate was good (2254/5794, 38.9%). The median task completion time was 3 (IQR 2-13) minutes, suggesting good system efficiency and effectiveness. The qualitative findings emphasized good user satisfaction. The identified themes suggested that the measurement system is acceptable, easy to use, and easy to access. Service users identified potential barriers and solutions to acceptability and ease of access. CONCLUSIONS: A mixed methods evaluation of an electronic measurement system for automated, real-time monitoring of patients' experience of SDM showed that usability among patients was high. Future pilot work will optimize the system for wider implementation to ultimately inform intervention development to improve SDM. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2023-079155.