2000-2020 NHIS Studies: Factors affecting medication adherence rate in the pediatric population with medical complexity

Introduction Children with medical complexity belong to a vulnerable patient population group that is defined by the interplay of chronic health conditions, high healthcare utilization, and severe limitations in cognitive and/or physical functioning. Members of this patient population often require a complex management and/or treatment regimen with the use of more than one medication. Pediatric nonadherence in medication can lead to increases in microbial resistance, adverse drug reactions, morbidity, and mortality. The consequences of this medication nonadherence may also cause slower recovery times, increased number of emergency department visits, and hospitalizations, which subsequently substantiates higher medical costs for families along with the healthcare system. General factors for pediatric medical adherence include age, culture, family structure, socioeconomic status, schedule of medication therapy, and taste/formulation of therapy. Continual studies on these medical adherence factors are of the utmost importance to mitigate nonadherence improving quality of life and reducing medical costs. This study examines the variables and confounding factors that may be responsible for the prevalence of nonadherence in this patient population. Methods Twelve primary articles using data collected through the National Health Interview Survey (NHIS) – focused on medication adherence secondary to medication therapy management (MTM) in the pediatric population across various chronic disease states –were examined and analyzed to collect the variables and factors of interest. Each article in the review was chosen to analyze a national representation of U.S. children between the years 2000-2020. The age perimeter was between ages zero (infants) to eighteen. Results Among the fifteen NHIS papers measuring medication adherence outcomes, three addressed financial and family disparities, three focused on the racial disparities’ association, and the remaining nine papers address other confounding factors (including but not limited to geographic location, patient education, and healthcare access). Results from the analysis confirmed the influence that racial/ethnic and/or socioeconomic disparities have on the medication adherence rate of the US pediatric population with medical complexity. Conclusion The medication adherence rate is affected by racial and ethnic disparities, financial hardships, socioeconomic status, family background education, poverty status, children’s health status, quality of patient education, and religious beliefs. This calls for more public health policies to alleviate the financial burden of medication costs, as well as efforts to improve medication education for the caregivers of children with medical complexity population in the U.S. The data-collecting phase of this research reveals the scarcity of studies on this topic – as reflected in the small number of articles found and reviewed. For a better understanding of the medication adherence rate among the medically complex pediatric population of the U.S., further research on this topic should be conducted

Towards Robust Aspect-based Sentiment Analysis through Non-counterfactual Augmentations

While state-of-the-art NLP models have demonstrated excellent performance for aspect based sentiment analysis (ABSA), substantial evidence has been presented on their lack of robustness. This is especially manifested as significant degradation in performance when faced with out-of-distribution data. Recent solutions that rely on counterfactually augmented datasets show promising results, but they are inherently limited because of the lack of access to explicit causal structure. In this paper, we present an alternative approach that relies on non-counterfactual data augmentation. Our proposal instead relies on using noisy, cost-efficient data augmentations that preserve semantics associated with the target aspect. Our approach then relies on modelling invariances between different versions of the data to improve robustness. A comprehensive suite of experiments shows that our proposal significantly improves upon strong pre-trained baselines on both standard and robustness-specific datasets. Our approach further establishes a new state-of-the-art on the ABSA robustness benchmark and transfers well across domains.Comment: 10pages,1 figure,10 table

Experimental investigation of freeze injury temperatures in trees and their contributing factors based on electrical impedance spectroscopy

In trees, injuries resulting from subfreezing temperatures can cause damage to the cellular biofilm system, metabolic functions, and fibrous reticulum, and even cell death. Investigating the occurrence of freezing damage and its contributing factors could help understand the mechanisms underlying freezing injury and prevent the subsequent damage in trees. To achieve this, a laboratory experiment was conducted using cut wood samples from Korean pine (Pinus koraiensis Siebold & Zucc) and Simon poplar (Populus simonii Carr.), and the effects of environmental freezing factors, including freezing temperatures, freezing duration, and cooling rate, on the temperature at which freezing injuries occur were examined using the electrical impedance spectroscopy (EIS) method. The semi-lethal temperature (LT50), as an indicator of freezing injury in wood tissue, was theoretically deduced based on the measured extracellular resistance (re) using EIS. The contributory factors to changes in LT50 were determined and their relationship was established. The results revealed that all freezing factors exhibited significant effects on electrical impedance characteristics (re, ri, and τ), significantly influencing the LT50 of the wood. Random forest (RF) and support vector machine (SVM) models were used to assess the contribution of the freezing factors and moisture content (MC). Among the factors examined, freezing duration had the greatest impact on LT50, followed by the MC, whereas the contribution of the cooling rate was minimal. The model accuracies were 0.89 and 0.86 for Korean pine and Simon poplar, respectively. The findings of our study illustrate that the occurrence of freezing injury in trees is primarily influenced by the duration of freezing at specific subzero temperatures. Slow cooling combined with prolonged freezing at low subzero temperatures leads to earlier and more severe freezing damage

Air pollution control or economic development? Empirical evidence from enterprises with production restrictions

Production restriction is an environmental regulation adopted in China to curb the air pollution of industrial enterprises. Frequent production restrictions may cause economic losses for enterprises and further hinder their green transformation. Polluting enterprises are faced with the dilemma of choosing environmental protection or economic development. Using panel data on industrial enterprises in China from 2016 to 2019, this paper evaluates the impact of production restrictions on both enterprises' environmental and economic performance with regression models. The results show that production restrictions significantly drop the concentrations of SO2 and NOx emitted from polluting enterprises. Meanwhile, production restrictions have significant negative effects on operating income, financial expenses, net profit, and environmental protection investment. The mechanism analysis reveals that production restrictions mitigate air pollutant concentrations by increasing the number of green patents and improving total factor productivity, which also verifies the Porter hypothesis. However, there is a masking mediating effect of environmental investment, which indicates that the reduction of environmental investment hinders the enterprise's efforts to control air pollution. In addition, heterogeneous analysis shows that the economic shock on microenterprises is larger than that on small enterprises. Implementing production restrictions for microenterprises may be a way to eliminate their backwards production capacity