Adult cancer patients' barriers to and satisfaction with care at a National Cancer Hospital in Vietnam.

STUDY OBJECTIVE: This study assessed the overall satisfaction with oncological care, including barriers to care, and identified its associated predictors among adult cancer patients in Vietnam. METHODS: In this cross-sectional study, we enrolled 300 adult cancer patients receiving inpatient care at a large urban oncological hospital between June and July 2022. Multivariable linear regression analyses examined associations between patient experiences and overall satisfaction ratings with cancer care. RESULTS: The mean overall satisfaction with oncological care was 8.82 out of 10, with 98.0% recommending this facility to their friends and family. In an adjusted model, being female (ß = 0.29, 95%CI: 0.04, 0.53), endorsing satisfaction with patient-nurse communication (ß = 0.33, 95%CI: 0.13, 0.53), patient-doctor communication (ß = 0.40, 95%CI: 0.11, 0.70), and psychoeducation about oncological medication management (ß = 0.30, 95%CI: 0.14, 0.45) were positively associated with overall ratings. In contrast, individuals with delays in treatment scheduling reported lower overall satisfaction with oncological care (ß = -0.38, 95%CI: -0.64, -0.13). Patients perceived health system, social/environmental, and individual barriers to care: worries about income loss due to attending treatment (43.3%); fear, depression, anxiety, and distress (36.8%); concerns about affordability of treatment (36.7%) and transportation problems (36.7%); and excessive waiting times for appointments (28.8%). CONCLUSION: This study showed high overall patient satisfaction with cancer care quality. Patient-centered communication strategies and psychoeducation about oncological medication management may be targeted to further enhance the cancer inpatient experience. Raising awareness about treatment options and services, and integrating mental health awareness into oncological care may ameliorate patient distress and facilitate greater satisfaction with oncological treatment processes.

A stochastic differential equation model for predator-avoidance fish schooling.

This paper presents a mathematical model based on stochastic differential equations (SDEs) to depict the dynamics of a predator-prey system in an aquatic environment characterized by schooling behavior among the prey. The model employs a particle-like approach, incorporating attractive and repulsive forces, akin to phenomena observed in molecular physics, to capture the interactions among the constituent units. Two hunting tactics of the predator, center-attacking and nearest-attacking strategies, are integrated into the model. Numerical simulations of this model unveil four distinct predator-avoidance patterns exhibited by schooling prey: Split and Reunion, Split and Separate into Two Groups, Scattered, and Maintain Formation and Distance. Our results also confirm the effectiveness of large groups of schooling prey in mitigating predation risk, consistent with real-life observations in natural aquatic ecosystems. These findings validate the accuracy and applicability of our model.

Fully Automatized Optimization of Ring-Opening Reactions in Lactone Derivatives via Two-Step Machine Learning.

Cyclization and cycloreversion of organic compounds are fundamental kinetic processes in the design of functional molecules, molecular machines, nanoscale sensors, and switches in the field of molecular and nanoelectronics. We present a fully automatic computational platform for the design of a class of five- and six-membered ring lactones by optimizing the ring-opening reaction rate. Starting from a minimal initial parent set, our algorithm generates iteratively cascades of pools of candidate lactone derivatives where optimization and down-selection are performed without human supervision. We employ the density functional theory combined with the transition state theory to elucidate the exact mechanism leading to the lactone ring-opening reaction. On the basis of the analysis of the reaction pathway and the frontier molecular orbitals, we identify a simple descriptor that can easily correlate with the reaction rate. Consequently, we can omit computationally expensive transition state calculations and deduce the reaction rate from simple ground-state and ionic calculations. To accelerate the platform, we use a data set of the order of 800 molecules to train machine learning models for the prediction of targeted chemical properties, reducing the computational time by a 90% factor. We developed an evolutionary algorithm capable of generating data sets 3 orders of magnitude larger than the initial parent set. Thus, we can explore a large domain of chemical space using minimal computational effort. Our entire platform is modular, and our current implementation for lactone can be further generalized to more complex systems via substitution of the quantum chemical and fingerprinting modules.

Mental health, functional impairment, and barriers to mental health access among cancer patients in Vietnam.

OBJECTIVE: This study evaluated the prevalence and severity of depression and anxiety symptomatology, barriers to mental health access, and correlates of functional impairment among cancer inpatients. METHODS: This cross-sectional study recruited adult cancer patients (N = 300) in June and July 2022 at the largest oncological hospital in Vietnam. Multivariable linear regression analyses examined the association between demographics, clinical characteristics, and patients' functional impairment. RESULTS: Approximately 46.3% and 27.0% showed some depression and anxiety symptomatology, while 8.0% and 3.0% experienced major depressive and anxiety symptoms, respectively. Patients reported the most impairment in mobility and capacity for life activities. More functional impairment was identified in patients with gastrointestinal cancers, those receiving radiation therapy alone, and those scoring higher on depression and anxiety than in those with cancers originating in the head, neck, or lung or those receiving chemotherapy alone. Reports of better overall health status were negatively associated with functional impairment. Patients reported extensive perceived barriers to seeking psychiatric care, including not knowing where to get mental health support (86.7%), wanting to manage mental health independently (73.7%), and thinking mental health will resolve on its own (73.7%), and denying mental health concerns (61.0%). CONCLUSION: High frequency and severity of depression and anxiety symptomatology underscore the importance of integrating mental health services into existing oncological treatment protocols. Increasing mental health literacy and provision of psychoeducation is critical to addressing barriers to mental health service access. Integration of functional impairment evaluations into hospital admission and discharge planning is also needed.

A stochastic differential equation model for the foraging behavior of fish schools.

Constructing models of living organisms locating food sources has important implications for understanding animal behavior and for the development of distribution technologies. This paper presents a novel simple model of stochastic differential equations for the foraging behavior of fish schools in a space including obstacles. The model is studied numerically. Three configurations of space with various food locations are considered. In the first configuration, fish swim in free but limited space. All individuals can find food with large probability while keeping their school structure. In the second and third configurations, they move in limited space with one and two obstacles, respectively. Our results reveal that the probability of foraging success is highest in the first configuration, and smallest in the third one. Furthermore, when school size increases up to an optimal value, the probability of foraging success tends to increase. When it exceeds an optimal value, the probability tends to decrease. The results agree with experimental observations.

Obstacle avoiding patterns and cohesiveness of fish school.

This paper is devoted to studying obstacle avoiding patterns and cohesiveness of fish school. First, we introduce a model of stochastic differential equations (SDEs) for describing the process of fish school's obstacle avoidance. Second, on the basis of the model we find obstacle avoiding patterns. Our observations show that there are clear four obstacle avoiding patterns, namely, Rebound, Pullback, Pass and Reunion, and Separation. Furthermore, the emerging patterns change when parameters change. Finally, we present a scientific definition for fish school's cohesiveness that will be an internal property characterizing the strength of fish schooling. There are then evidences that the school cohesiveness can be measured through obstacle avoiding patterns.