Subsequent Decisions Research Articles

Short-term memory effects of eco-labeling: Evidence from the perceived environmental friendliness of sequential consumer behavior

Can memory of eco-labeling bias how consumption is perceived and influence subsequent consumer decisions? We report three experiments showing that the perceived environmental friendliness of simulated shopping sequences is disproportionately influenced by what happens at the end of the sequence. For example, sequences that ended with a high carbon footprint item were perceived as less environmentally friendly than other sequences with the same content but with items in different order—a recency effect (Experiments 1–3). Judgments depended more on how often environmentally significant items were purchased than on the quantity of those items (Experiment 2). Furthermore, after completing a shopping sequence that was perceived as relatively harmful to the environment, participants were more prone to select a comparably expensive eco-labeled item over a cheaper but less environmentally friendly item in subsequent purchase decisions—a spillover effect (Experiment 3). The results stress the role of memory in environmentally significant consumer behavior.

Systematic comparison of resilience scales using retrospective reports: A practical case study using South African data

The availability of different scales measuring similar constructs challenges scientists and practitioners when it comes to choosing the most appropriate instrument to use. As a result, systematic comparison frameworks have been developed to guide such decisions. The Consensus-based Standard for the Selection of Health Measurement Instruments (COSMIN) is one example of such a framework to examine the quality of psychometric studies. This article aimed, firstly, to explore the psychometric characteristics of resilience measures used in the South African Navy (SAN), in that context. Secondly, it aimed to illustrate the application of the COSMIN guide for comparing psychometric scales and employing data from the aforementioned resilience measures, as a practical case study. The study drew on both published and unpublished data from seven SAN samples, using eight psychometric scales associated with resilience. It assessed structural validity, construct validity, internal reliability and predictive ability. The outcomes were tabulated, and the COSMIN criteria were applied to each data point. All eight scales provided some degree of evidence of validity. However, it was at times difficult to differentiate between the scales when using the COSMIN guidelines. In such cases, more nuanced criteria were necessary to demonstrate more clearly the differences between the psychometric characteristics of the scales and ease in subsequent decision-making.Contribution: This article illustrated the application of COSMIN guidelines to systematically compare the quality of psychometric study outcomes on local South African data. It further offered evidence of validity for a range of resilience-related measures in a South African context.

Identifying the factors affecting financial toxicity status in patients with middle and advanced colorectal cancer: a cross-sectional study.

Colorectal cancer (CRC) ranks as the second most prevalent type of cancer in China. The financial implications of treatment are a significant factor to be taken into account for patients diagnosed with middle and advanced stages of colorectal cancer (III-IV CRC). The research aims to explore current financial toxicity (FT) conditions and analyze factors that may influence it in patients with middle and advanced CRC. This is a cross-sectional survey. The participants of the study were individuals diagnosed with middle and advanced colorectal cancer who were admitted to the hospital between January and June 2023. The cross-sectional survey utilized a variety of instruments, including a general information questionnaire, a cancer patient report outcome economic toxicity scale, a medical coping style questionnaire, an Anderson symptom assessment scale, a disease shame scale, and a social support scale. Multiple linear regression analysis was employed to examine the factors influencing FT. A cohort of 264 patients diagnosed with stage III-IV CRC were included in the study. The majority of patients with intermediate and advanced CRC (87.1%, n = 230) reported experiencing substantial financial strain. Multivariate analysis revealed that factors influencing FT included low family monthly income, out-of-pocket expenses, unemployment, undergoing surgical treatment, the level of stigma, and the severity of symptoms (P < 0.001). Patients with stage III-IV cancer (CRC) demonstrate increased levels of financial toxicity (FT), a common occurrence in individuals with moderate to severe CRC. In patients with stage III-IV CRC, the presence of FT is correlated with various factors including family monthly income, medical payment methods, work status, surgical treatment, stigma levels, and symptom severity. These characteristics may serve as influencing factors for subsequent treatment decisions.

Russian Pravda as a primary source of administrative law and process in ancient Russia

Russian Truth is the oldest monument of the law of feudal Rus’. It reflects the growth of princely power and the expansion of the princely court. This study is devoted to identifying the features of law and legal proceedings in this era. Like the ancient Laws of the XII tables in Ancient Rome and the Babylonian laws of King Hamurabi (Hamurabi), to which our study was devoted. Russian Truth is also a judge. In it we meet the rules of law, which we now call administrative law and process. Separate historical epochs are mixed up in Russkaya Pravda, there is no systematization of norms. A separate part of the truth is called “The Court of Yaroslav Vladimirovich.” Russkaya Pravda does not give us a complete account of the organization of the princely court. Separate princely decisions became the norm for subsequent court decisions. So, the prince sets penalties for killing people depending on their position. Pravda Yaroslavichi forbids blood feuds and introduces a fine instead. Litigation under Russkaya Pravda is adversarial, which establishes pre-trial procedures. The relationship between the plaintiffs and the defendants is clarified. This order is called “arching” and “persecution of the trace.” Competitiveness arises from those forms of struggle that existed even in a tribal society, when relations were sorted out by force. The study showed that the law according to Russian Pravda has gone ahead of the primitive customs of more ancient times and represents a developed system, where there was a court, a process, a system of evidence and punishments.

Vaccinating the Frontlines: A Qualitative Exploration of Hospital Healthcare Worker Perspectives on Influenza and COVID-19 Immunization.

Although they face higher occupational risk of contracting viral respiratory infections, hospital healthcare worker vaccine hesitancy persists. While most studies have used survey methods to quantify the prevalence of and reasons for healthcare worker vaccine hesitancy, this study employs a qualitative approach to understand their attitudes and beliefs associated with influenza and COVID-19 vaccination. To understand frontline healthcare worker experiences and perspectives on influenza and COVID-19 vaccination, 30 semi-structured interviews were conducted in summer/fall 2022 with staff recruited from two Johns Hopkins hospitals in Maryland. An in-depth, key informant interview was conducted with an expert in public health audience engagement. Interviews were audio recorded and transcribed for thematic and Framework analysis using NVivo software (QSR International, Melbourne, Australia). Healthcare workers engaged in little influenza vaccine information seeking due to their familiarity with the disease and low perceived disease severity. Approximately half (n=16) of healthcare workers reported no vaccine hesitancy towards influenza or COVID-19 vaccines. No physicians or physician assistants expressed any vaccine hesitancy, while most nurses expressed some (n=10). More than half of the women (n=14) expressed COVID-19 vaccine hesitancy compared to none of the men. Structural factors including hospital tier, unit assignment, and professional role influenced perceived risk of disease exposure and subsequent healthcare worker vaccination decisions. Institutional policies, including mandates and a pro-vaccine environment encouraged vaccination uptake. Healthcare workers reported being more receptive to vaccine messaging that focused on protection from disease, scientific and public health data and their heightened occupational exposure to pathogens. Despite their medical knowledge, healthcare workers are susceptible to vaccine hesitancy. Strategies to address specific concerns are needed and can be informed by our findings. A flexible and multi-pronged approach that considers individual anxieties, workplace structures, and the need for open communication with tailored messaging is necessary to promote vaccine acceptance in healthcare settings. What is already known on this topic: Healthcare worker vaccine hesitancy has been associated with many factors including race, gender, age and concerns about vaccine safety.What this study adds: Much of the research on healthcare worker vaccine hesitancy has used surveys and questionnaires giving a broad description of the prevalence and patterns of vaccine hesitancy in the healthcare workforce. This qualitative study examines vaccine behavior (rather than merely intent) through a cross comparison of healthcare workers' experiences and attitudes towards influenza and COVID-19 vaccination.How this study might affect research, practice or policy: Study findings can be used to help tailor vaccine messaging to hospital healthcare workers which could offset concerns regarding vaccine efficacy and risk, to promote vaccine uptake.

Inquiry-Guided Experiential Learning in FASB Codification Research: An Investment Portfolio Simulation Project

We designed and implemented an inquiry-guided experiential learning project in which students researched and interpreted accounting standards from FASB Accounting Standards Codification to support their applications and assessment of the accounting treatment in a hands-on quasi-real-world simulation for investment activities. Specifically, in the project’s first phase, students explored, researched, identified, and interpreted the related accounting standards from the Codification for a fictional client’s investment activities. Students then ran an investment portfolio simulation in the second phase, in which they (1) created organic investment activities, (2) made authentic applications of accounting standards, (3) analyzed and evaluated the impact on self-prepared financial reports, and (4) modified subsequent investment decisions. Most students were well motivated to explore and self-study the accounting concepts and procedures. They considered the project relevant, interesting, and effective. Their performance in project knowledge tests improved student learning along factual, conceptual, procedural, and metacognition knowledge dimensions. They were willing to put time and effort into the project and would recommend it for future use.

Emotion regulation flexibility: EEG/EMG predictors and consequences of switching between reappraisal and distraction strategies.

Flexible use of emotion regulation (ER) strategies is central to mental health. To advance our understanding of what drives adaptive strategy-switching decisions, in this preregistered study, we used event-related potentials (late positive potential, LPP and stimulus preceding negativity, SPN) and facial electromyography (EMG corrugator activity) to test the antecedents and consequences of switching to an alternative ER strategy. Participants (N = 63, Mage = 24.8 years, all female) passively watched and then implemented an instructed ER strategy (reappraisal or distraction) in response to high-intensity negative pictures that were either easy or difficult to reinterpret (high or low reappraisal affordance, respectively). Next, they decided to "switch from" or "maintain" the instructed strategy and subsequently implemented the chosen strategy. Reappraisal affordance manipulations successfully induced switching. Regarding antecedents, switching was predicted by the reduced ER efficacy of the current strategy (corrugator, but not LPP). Switching to distraction was additionally predicted by increased responses to the stimulus during passive viewing (corrugator and LPP) and increased anticipatory effort in implementing reappraisal (SPN). Concerning consequences, switching to distraction improved, whereas switching to reappraisal impaired post-choice ER effects (LPP). However, starting with reappraisal was overall more effective than starting with distraction, irrespective of the subsequent decision (corrugator). Our results suggest that switching between ER strategies occurs in accordance with situational demands (stimulus affordances) and is predicted by reduced peripheral physiological ER efficacy. However, only switching to distraction leads to improved regulatory effects. These insights provide neurocognitively grounded starting points for developing interventions targeting ER flexibility.

P-497 Increasing use of pan-ethnic carrier screening for donor gametes creates new challenges for clinics and recipient counselling

Abstract Study question How can clinics support recipients to understand a positive or negative carrier status following pan-ethnic carrier screening. Summary answer A combination of recipient testing and genetic counselling enables the use of donor sperm irrespective of pan-ethnic screening results. What is known already Data reported by the HFEA, UK reveals that in 2020, more than half of new donor registrations were from donor imports - 48% were American or Danish in origin, where the level of genetic screening for recessive conditions can vary from 3 to 502 genes. Donor banks generally state that donors are screened to professional guidelines for the countries they supply. Variations in the practice for carrier screening of gamete donors and how this information is shared and charged can be opaque to clinics and complex for recipients to navigate without specialist support to understand relevance and reproductive risk. Study design, size, duration This study reports on the number of genetic counselling requests from several IVF clinic referrals in the UK for the period Jan 2020 - Dec 2023. A total of 412 recipients interested in purchasing samples from donors identified as a positive carrier of one or more recessive condition(s) after undergoing extended carrier screening. Referrals for ECS negative donors were not received. Participants/materials, setting, methods Recipients were provided with the opportunity of genetic counselling to include the meaning of the carrier status, risk estimates, and options. Recipients were then given the opportunity to review the consultation report and were supported through their subsequent decision-making. The recipient’s choice to accept the risk for using the donor or proceed to counter-screening was evaluated to give insight into the recipient decision-making for accepting risk or wishing to undertake carrier screening. Main results and the role of chance UK screening recommendations cumulatively account for only 9.3% of identified mutations within a sperm donor applicant population at a single commercial US sperm bank screened using ECS, highlighting international inconsistencies in donor recruitment and acceptance criteria. 15.3 % (n = 63) of recipients elected to be screened for the conditions their donor was a carrier for, with most opting to be screened on a matched gene panel to provide information for a child and allow future matching with an alternative donor. 84.7% (n = 359) proceeded with treatment without counter screening appreciating their relatively low reproductive risk. Patients who undertake consultation with a genetic professional can understand their reproductive risk for autonomous decision-making, indicating ECS positive results are not a barrier to donor gamete selection for treatment. Limitations, reasons for caution ECS panels are variable by commercial provider, donor banks may vary their carrier screening policy or commercial ECS options over time, limiting the findings to the time frame in which the abstract was written Wider implications of the findings Review and implementation of carrier screening guidelines are required to ensure consistency and transparency with access to suitably qualified genetics professionals to provide information counselling and genetic testing options. This allows recipients to maintain a level of autonomy for donor selection and may ultimately widen the available donor pool. Trial registration number not applicable

Deep Residual Learning-Based Classification with Identification of Incorrect Predictions and Quantification of Cellularity and Nuclear Morphological Features in Digital Pathological Images of Common Astrocytic Tumors.

Interobserver variations in the pathology of common astrocytic tumors impact diagnosis and subsequent treatment decisions. This study leveraged a residual neural network-50 (ResNet-50) in digital pathological images of diffuse astrocytoma, anaplastic astrocytoma, and glioblastoma to recognize characteristic pathological features and perform classification at the patch and case levels with identification of incorrect predictions. In addition, cellularity and nuclear morphological features, including axis ratio, circularity, entropy, area, irregularity, and perimeter, were quantified via a hybrid task cascade (HTC) framework and compared between different characteristic pathological features with importance weighting. A total of 95 cases, including 15 cases of diffuse astrocytoma, 11 cases of anaplastic astrocytoma, and 69 cases of glioblastoma, were collected in Taiwan Hualien Tzu Chi Hospital from January 2000 to December 2021. The results revealed that an optimized ResNet-50 model could recognize characteristic pathological features at the patch level and assist in diagnosis at the case level with accuracies of 0.916 and 0.846, respectively. Incorrect predictions were mainly due to indistinguishable morphologic overlap between anaplastic astrocytoma and glioblastoma tumor cell area, zones of scant vascular lumen with compact endothelial cells in the glioblastoma microvascular proliferation area mimicking the glioblastoma tumor cell area, and certain regions in diffuse astrocytoma with too low cellularity being misrecognized as the glioblastoma necrosis area. Significant differences were observed in cellularity and each nuclear morphological feature among different characteristic pathological features. Furthermore, using the extreme gradient boosting (XGBoost) algorithm, we found that entropy was the most important feature for classification, followed by cellularity, area, circularity, axis ratio, perimeter, and irregularity. Identifying incorrect predictions provided valuable feedback to machine learning design to further enhance accuracy and reduce errors in classification. Moreover, quantifying cellularity and nuclear morphological features with importance weighting provided the basis for developing an innovative scoring system to achieve objective classification and precision diagnosis among common astrocytic tumors.

Health professionals implicit bias of patients with low socioeconomic status (SES) and its effects on clinical decision-making: a scoping review

ObjectivesResearch indicates that people with lower socioeconomic status (SES) receive inferior healthcare and experience poorer health outcomes compared with those with higher SES, in part due to health professional (HP)...

Unsupervised gas pipeline network leakage detection method based on improved graph deviation network

Historical data has shown that the natural gas pipeline network, as a critical urban lifeline system, is susceptible to disasters such as earthquakes resulting in leakage. Graph neural network modeling provides frontier rapid detection solutions for pipeline leakage; however, the challenges of collecting gas network anomaly data for training limit the precision and robustness of current model. This research proposes an unsupervised gas leakage detection and localization method based on a contained preprocessing process, with a graph deviation model that combines a structural learning approach with a graph neural network to model the spatial dependence of the sensors based on an attention mechanism, and variational inference models the posterior distributions of the hyper-parameters to optimize the model and improve the model precision. Meanwhile, in the preprocessing stage, the automatic optimization strategy of Northern Goshawk Optimization (NGO) for the best parameters K and ɑ in the Variable Mode Decomposition (VMD) efficiently extracts the valid signals and ensures that the model gives full play to the detection and localization effectiveness. The gas pipeline network dataset constructed by Pipeline Studio was used for comparing the performance of the model in this study with other frontier models. The results demonstrate that the model in this research has competitive detection Precision (93.31%), Recall (70.82%), and F1-score (0.81), and the posterior distribution of the model parameters strengthens the gas leakage localization precision, which provides a comprehensive solution for subsequent decision-making and reduces the hidden hazard of leakage effectively.

Earnings mean reversion and dynamic optimal capital structure

We formulate a trade-off model that integrates mean reversion in earnings, encompassing dynamic financing decisions that entail both the initial leverage selection and the subsequent decision related to the financing of a growth option. We identify that higher earnings mean reversion speed increases both initial and subsequent leverage ratios for growth option financing and accelerates investment, revealing the volatility-mitigating role of mean reversion speed. Furthermore, our analysis reveals a U-shaped relation between profitability and leverage, influenced by the presence of growth options. In contrast, higher long-term profitability has a positive relationship with leverage, highlighting the differential impact of long-term versus contemporaneous profitability on leverage. The model also yields further implications for corporate policies regarding debt priority structure, investment timing, default thresholds, and credit spreads, contingent on earnings mean reversion dynamics. Our empirical analysis reveals the prevalence of mean reversion in earnings among US firms and provides a comparison of capital structure decisions of firms with mean reverting earnings against firms having non-stationary earnings dynamics.

Risk analysis and assessment of underwater glider mission failure using Dynamic Bayesian Network method

The Autonomous Underwater Glider (AUG), with its extended operational endurance, encounters various uncertain risks during diverse mission tasks. Therefore, conducting dynamic risk analysis is crucial for implementing subsequent decisions and improving equipment safety. This paper combines Fault Tree Analysis (FTA) and Dynamic Bayesian Network (DBN) to develop a customized dynamic risk assessment method for AUG task failure under multiple risk factors. Firstly, preliminary risk factors are identified by FTA using existing experimental data. Next, transformation rules are constructed to map FTA into a basic DBN model. Then, parameters such as conditional probabilities are determined through logic gates and parameter learning, and the proposed model is validated based on axioms. Finally, key risk factors are identified based on actual failure data. The research results indicate that the key risk factors leading to AUG task failure are progressive abnormalities such as biofouling and ocean current disturbance. The method proposed in this paper can achieve dynamic risk assessment, providing strong references for operators in making decisions for subsequent tasks.

GeneWorker: An end-to-end robotic reinforcement learning approach with collaborative generator and worker networks

Reinforcement learning aided by the skill conception exhibits potent capabilities in guiding autonomous agents toward acquiring meaningful behaviors. However, in the current landscape of reinforcement learning, a skill is often merely a rudimentary abstraction of a sequence of primitive actions, serving as a component of the input to policy networks with fixed network parameters. This rigid methodology presents obstacles when attempting to integrate with burgeoning techniques such as meta-learning and large language models. To address this issue, we introduce a unique neural skill representation that abstracts the activation of neurons in each neural layer. Based on this, a novel end-to-end robotic reinforcement learning algorithm is proposed, in which two sub-networks, i.e., generator and worker networks, implement collaborative inferences via neural skills. Specifically, the generator produces a series of multi-spatial neural skills, providing efficient guidance for subsequent decision-making; by integrating these skills, the worker can determine its own network weights and biases to cope with various environmental conditions. Therefore, actions can be sampled with flexibly changeable network parameters through the collaboration between generator and worker networks. The experiments demonstrate that GeneWorker can achieve a mean success rate of over 90.67% on continuous robotic tasks and outperforms previous state-of-the-art methods by a minimum of 54% on the pick-and-place task.

The Homunculus of unspecific bone uptakes associated with PSMA-targeted tracers: a systematic review-based definition.

Prostate-Specific Membrane Antigen (PSMA)-targeted Positron Emission Tomography (PET) has revolutionised prostate cancer (PCa) diagnosis and treatment, offering superior diagnostic accuracy over traditional methods and enabling theragnostic applications. However, a significant diagnostic challenge has emerged with identifying unspecific bone uptakes (UBUs), which could lead to over-staging and inappropriate treatment decisions if misinterpreted. This systematic review explores the phenomenon of UBUs in PCa patients undergoing PSMA-PET imaging. Studies assessing the prevalence, topographical distribution, and potential clinical implications of UBUs were selected according to the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) method and evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. The percentage of PCa patients with UBUs on PSMA-PET scans ranged from 0 to 71.7%, depending on the radiopharmaceutical used, with [18F]PSMA-1007 showing the highest incidence. The ribs are the primary site of UBUs across all PSMA-targeted radiopharmaceuticals. The spine is the second most frequent UBU site for [68Ga]Ga-PSMA-11, [18F]DCFPyL, [18F]rhPSMA-7, while the pelvic girdle represents the second most frequent site for [18F]PSMA-1007. The average maximum Standardized Uptake Value (SUVmax) of UBUs varied from 3.4 to 7.7 and was generally lower than that of bone metastases. Our findings underscore the need for heightened awareness and precise interpretation of UBUs to avoid potential over-staging and subsequent inappropriate treatment decisions. Considering the radiopharmaceutical used, PET-derived semiquantitative parameters, the topographical distribution of UBUs, and accurately evaluating the pre-test probability based on clinical and laboratory parameters may aid nuclear medicine physicians in interpreting PSMA-PET findings.

Markov decision process framework of optimal energy dispatch in a smart data center with uninterruptible power supplies

This paper examines the use of an Uninterruptible Power Supply (UPS) to enhance the operational efficiency of data centers. It focuses on developing an optimal energy scheduling strategy for a data center equipped with UPS, using the Markov decision process (MDP) framework. The MDP framework simulates the decision-making process involved in minimizing energy costs. Each unit’s available power output in the data center is treated as a Markov state, taking into account the uncertainty associated with renewable distributed generation. This uncertainty drives the system to transition to other Markov states in subsequent decision times. A recursive optimization model is established for each Markov state at each decision time to guide state-based operations, which includes determining the unit output while considering both current and future costs. The challenge of dealing with high dimensionality, arising from a substantial number of states and actions in the model, is effectively addressed by adopting an approximate dynamic programming (ADP) method. This approach incorporates decision-state and forwards dynamic algorithms to tackle the complexity of the MDP-based model. By employing ADP, the computational burden is reduced, enabling efficient and practical solutions to be obtained.

Production Location Selecting and Subsequent Production Decision Making for Sport Obermeyer

This paper revolved around two core research issues: production location selection and subsequent production decisions. The aim of the study was to provide a detailed analysis of Sport Obermeyer's data from 1992 to 1995 in a new way, hoping to assist companies facing similar challenges. The paper took Cost, Quality, Lead time and Minimum order quantity as bridges to the four main factors affecting the choice of production location. It detailed the advantages and disadvantages of the two production locations: Hong Kong and China. Then, with the aid of the Newsvendor model, the mismatch cost ratio for the 10 styles was determined. Ultimately, using the coefficient of variance for comparison and confirmation of the mismatch cost ratio results, the paper helped Sport Obermeyer analyze which styles of parkas had low-risk and low-uncertainty demand, and which had high-risk and high-uncertainty. The paper then combined the characteristics of the two production locations and assisted Sport Obermeyer in making subsequent production decisions. Five styles of parkas suitable for production in China and five styles suitable for production in Hong Kong were identified, ensuring stable profits and deliveries for Sport Obermeyer.

Production Location Selecting and Subsequent Production Decision Making for Sport Obermeyer

This paper revolved around two core research issues: production location selection and subsequent production decisions. The aim of the study was to provide a detailed analysis of Sport Obermeyer's data from 1992 to 1995 in a new way, hoping to assist companies facing similar challenges. The paper took Cost, Quality, Lead time and Minimum order quantity as bridges to the four main factors affecting the choice of production location. It detailed the advantages and disadvantages of the two production locations: Hong Kong and China. Then, with the aid of the Newsvendor model, the mismatch cost ratio for the 10 styles was determined. Ultimately, using the coefficient of variance for comparison and confirmation of the mismatch cost ratio results, the paper helped Sport Obermeyer analyze which styles of parkas had low-risk and low-uncertainty demand, and which had high-risk and high-uncertainty. The paper then combined the characteristics of the two production locations and assisted Sport Obermeyer in making subsequent production decisions. Five styles of parkas suitable for production in China and five styles suitable for production in Hong Kong were identified, ensuring stable profits and deliveries for Sport Obermeyer.

Intermediate Judgments and Trust in Artificial Intelligence-Supported Decision-Making.

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.

ROLE OF ULTRASONOGRAPHY IN RESPONSE ASSESSMENT FOLLOWING NEOADJUVANT CHEMOTHERAPY IN LOCALLY ADVANCED BREAST CARCINOMA: EXPERIENCE FROM A TERTIARY CARE CENTER

Objective: Neo-adjuvant chemotherapy (NACT) has a pivotal role in the treatment of locally advanced breast carcinoma (LABC). In this study, we assess the efficiency of ultrasound in the response assessment of NACT in patients with LABC using RECIST criteria and its correlation to the final histopathological report. Methods: 40 patients with LABC underwent clinical examination and ultrasonography (USG) of the bilateral breast and axilla before starting NACT. After receiving three cycles of NACT, a repeat USG and clinical examination were done to assess the response to chemotherapy. Patients with responsive disease underwent radical surgery, and we correlate the findings of histopathological examination (HPE) with those of post-NACT USG findings. Results: After three cycles of NACT, clinical examination showed a complete response in 15 (37.5%) patients and a partial response in 21 (52.5%) patients. While USG detected a complete response in 8 (20%) patients and a partial response in 28 (70%) patients, seven patients, in whom clinical examination did not find any disease, were detected by USG. HPE showed a complete pathological response in 5 specimens, and in the rest of 31 cases, HPE revealed a residual tumor. USG did not miss any of the pCR cases but overestimated CR cases by 9% (3 patients). On the other hand, all partial response diagnoses by USG were acknowledged by HPE. Conclusion: To conclude, it can be said that USG can be used as an effective radiological tool for response assessment and subsequent treatment decisions, especially in places where there is a lack of infrastructure and affordability.