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Applied Clinical Informatics May 2021To examine pediatricians' perspectives on administrative tasks including electronic health record (EHR) documentation burden and their effect on work-life balance and...
OBJECTIVES
To examine pediatricians' perspectives on administrative tasks including electronic health record (EHR) documentation burden and their effect on work-life balance and life and career satisfaction.
METHODS
We analyzed 2018 survey data from the American Academy of Pediatrics (AAP) Pediatrician Life and Career Experience Study (PLACES), a longitudinal cohort study of early and midcareer pediatricians. Cohorts graduated from residency between 2002 and 2004 or 2009 and 2011. Participants were randomly selected from an AAP database (included all pediatricians who completed U.S. pediatric residency programs). Four in 10 pediatricians (1,796 out of 4,677) were enrolled in PLACES in 2012 and considered participants in 2018. Data were weighted to adjust for differences between study participants and the overall population of pediatricians. Chi-square and multivariable logistic regression examined the association of EHR burden on work-life balance (three measures) and satisfaction with work, career, and life (three measures). Responses to an open-ended question on experiences with administrative tasks were reviewed.
RESULTS
A total of 66% of pediatrician participants completed the 2018 surveys (1,192 of 1,796; analytic sample = 1,069). Three-fourths reported EHR documentation as a major or moderate burden. Half reported such burden for billing and insurance and 42.7% for quality and performance measurement. Most pediatricians reported satisfaction with their jobs (86.7%), careers (84.5%), and lives (66.2%). Many reported work-life balance challenges (52.5% reported stress balancing work and personal responsibilities). In multivariable analysis, higher reported EHR burden was associated with lower scores on career and life satisfaction measures and on all three measures of work-life balance. Open-ended responses ( = 467) revealed several themes. Two predominant themes especially supported the quantitative findings-poor EHR functionality and lack of support for administrative burdens.
CONCLUSION
Most early to midcareer pediatricians experience administrative burdens with EHRs. These experiences are associated with worse work-life balance including more stress in balancing responsibilities and less career and life satisfaction.
Topics: Child; Electronic Health Records; Humans; Job Satisfaction; Longitudinal Studies; Pediatricians; Personal Satisfaction; Surveys and Questionnaires; United States; Work-Life Balance
PubMed: 34341980
DOI: 10.1055/s-0041-1732402 -
Journal of Neuroengineering and... Jun 2019Application of virtual reality (VR) to rehabilitation is relatively recent with clinical implementation very rapidly following technological advancement and scientific... (Review)
Review
BACKGROUND
Application of virtual reality (VR) to rehabilitation is relatively recent with clinical implementation very rapidly following technological advancement and scientific discovery. Implementation is often so rapid that demonstrating intervention efficacy and establishing research priorities is more reactive than proactive. This study used analytical tools from information science to examine whether application of VR to rehabilitation has evolved as a distinct field of research or is primarily a methodology in core disciplines such as biomedical engineering, medicine and psychology.
METHODS
The analysis was performed in three-stages: 1) a bibliographic search in the ISI Web of Science database created an initial corpus of publications, 2) the corpus was refined through topic modeling, and 3) themes dominating the corpus from the refined search results were identified by topic modeling and network analytics. This was applied separately to each of three time periods: 1996 to 2005 (418 publications), 2006 to 2014 (1454 publications), and 2015 to mid-2018 (1269 publications).
RESULTS
Publication rates have continuously increased across time periods with principal topics shifting from an emphasis on computer science and psychology to rehabilitation and public health. No terminology specific to the field of VR-based rehabilitation emerged; rather a range of central concepts including "virtual reality", "virtual gaming", "virtual environments", "simulated environments" continue to be used. Communities engaged in research or clinical application of VR form assemblages distinguished by a focus on physical or psychological rehabilitation; these appear to be weakly linked through tele-rehabilitation.
CONCLUSIONS
Varying terms exemplify the main corpus of VR-based rehabilitation and terms are not consistent across the many scientific domains. Numerous distinguishable areas of research and clinical foci (e.g., Tele-rehabilitation, Gait & Balance, Cognitive Rehabilitation, Gaming) define the agenda. We conclude that VR-based rehabilitation consists of a network of scientific communities with a shared interest in the methodology rather than a directed and focused research field. An interlinked team approach is important to maintain scientific rigor and technological validity within this diverse group. Future studies should examine how these interdisciplinary communities individually define themselves with the goals of gathering knowledge and working collectively toward disseminating information essential to associated research communities.
Topics: Humans; Rehabilitation; Terminology as Topic; Virtual Reality
PubMed: 31226995
DOI: 10.1186/s12984-019-0552-6 -
Mass Spectrometry Reviews Aug 2022Aroma determination in alcoholic beverages has become a hot research topic due to the ongoing effort to obtain quality products, especially in a globalized market.... (Review)
Review
Aroma determination in alcoholic beverages has become a hot research topic due to the ongoing effort to obtain quality products, especially in a globalized market. Consumer satisfaction is mainly achieved by balancing several aroma compounds, which are mixtures of numerous volatile molecules enclosed in challenging matrices. Thus, sample preparation strategies for quality control and product development are required. They involve several steps including copious amounts of hazardous solvents or time-consuming procedures. This is bucking the trend of the ever-increasing pressure to reduce the environmental impact of analytical chemistry processes. Hence, the evolution of sample preparation procedures has directed towards miniaturized techniques to decrease or avoid the use of hazardous solvents and integrating sampling, extraction, and enrichment of the targeted analytes in fewer steps. Mass spectrometry coupled to gas or liquid chromatography is particularly well suited to address the complexity of these matrices. This review surveys advancements of green miniaturized techniques coupled to mass spectrometry applied on all categories of odor-active molecules in the most consumed alcoholic beverages: beer, wine, and spirits. The targeted literature consider progresses over the past 20 years.
PubMed: 35980114
DOI: 10.1002/mas.21802 -
The Journal of Physical Chemistry. B Aug 2019The coassembly of different building blocks into supramolecular copolymers provides a promising avenue to control their properties and to thereby expand the potential of...
The coassembly of different building blocks into supramolecular copolymers provides a promising avenue to control their properties and to thereby expand the potential of supramolecular polymers in applications. However, contrary to covalent copolymerization which nowadays can be well controlled, the control over sequence, polymer length, and morphology in supramolecular copolymers is to date less developed, and their structures are more determined by the delicate balance in binding free energies between the distinct building blocks than by kinetics. Consequently, to rationalize the structures of supramolecular copolymers, a thorough understanding of their thermodynamic behavior is needed. Though this is well established for single-component assemblies and over the past years several models have been proposed for specific copolymerization cases, a generally applicable model for supramolecular cooperative copolymers is still lacking. Here, we provide a generalization of our earlier mass-balance models for supramolecular copolymerizations that encompasses all our earlier models. In this model, the binding free energies of each pair of monomer types in each aggregate type can be set independently. We provide scripts to solve the model numerically for any (co)polymerization of one or two types of monomer into an arbitrary number of distinct aggregate types. We illustrate the applicability of the model on data from literature as well as on new experimental data of triarylamine triamide-based copolymers in three distinct solvents. We show that apart from common properties such as the degree of polymerization and length distributions, our approach also allows us to investigate properties such as the copolymer microstructure, that is, the internal ordering of monomers within the copolymers. Moreover, we show that in some cases, also intriguing analytical approximations can be derived from the mass balances.
PubMed: 31287320
DOI: 10.1021/acs.jpcb.9b04373 -
Journal of Big Data 2021Data-driven innovation is propelled by recent scientific advances, rapid technological progress, substantial reductions of manufacturing costs, and significant demands...
Data-driven innovation is propelled by recent scientific advances, rapid technological progress, substantial reductions of manufacturing costs, and significant demands for effective decision support systems. This has led to efforts to collect massive amounts of heterogeneous and multisource data, however, not all data is of equal quality or equally informative. Previous methods to capture and quantify the utility of data include value of information (VoI), quality of information (QoI), and mutual information (MI). This manuscript introduces a new measure to quantify whether larger volumes of increasingly more complex data enhance, degrade, or alter their information content and utility with respect to specific tasks. We present a new information-theoretic measure, called Data Value Metric (DVM), that quantifies the useful information content (energy) of large and heterogeneous datasets. The DVM formulation is based on a regularized model balancing data analytical value (utility) and model complexity. DVM can be used to determine if appending, expanding, or augmenting a dataset may be beneficial in specific application domains. Subject to the choices of data analytic, inferential, or forecasting techniques employed to interrogate the data, DVM quantifies the information boost, or degradation, associated with increasing the data size or expanding the richness of its features. DVM is defined as a mixture of a fidelity and a regularization terms. The fidelity captures the usefulness of the sample data specifically in the context of the inferential task. The regularization term represents the computational complexity of the corresponding inferential method. Inspired by the concept of information bottleneck in deep learning, the fidelity term depends on the performance of the corresponding supervised or unsupervised model. We tested the DVM method for several alternative supervised and unsupervised regression, classification, clustering, and dimensionality reduction tasks. Both real and simulated datasets with weak and strong signal information are used in the experimental validation. Our findings suggest that DVM captures effectively the balance between analytical-value and algorithmic-complexity. Changes in the DVM expose the tradeoffs between algorithmic complexity and data analytical value in terms of the sample-size and the feature-richness of a dataset. DVM values may be used to determine the size and characteristics of the data to optimize the relative utility of various supervised or unsupervised algorithms.
PubMed: 34777945
DOI: 10.1186/s40537-021-00446-6 -
Methodist DeBakey Cardiovascular Journal 2023Rapid advancements in artificial intelligence (AI) have revolutionized numerous sectors, including medical research. Among the various AI tools, OpenAI's ChatGPT, a... (Review)
Review
Rapid advancements in artificial intelligence (AI) have revolutionized numerous sectors, including medical research. Among the various AI tools, OpenAI's ChatGPT, a state-of-the-art language model, has demonstrated immense potential in aiding and enhancing research processes. This review explores the application of ChatGPT in medical hospital level research, focusing on its capabilities for academic writing assistance, data analytics, statistics handling, and code generation. Notably, it delves into the model's ability to streamline tasks, support decision making, and improve patient interaction. However, the article also underscores the importance of exercising caution while dealing with sensitive healthcare data and highlights the limitations of ChatGPT, such as its potential for erroneous outputs and biases. Furthermore, the review discusses the ethical considerations that arise with AI use in health care, including data privacy, AI interpretability, and the risk of AI-induced disparities. The article culminates by envisioning the future of AI in medical research, emphasizing the need for robust regulatory frameworks and guidelines that balance the potential of AI with ethical considerations. As AI continues to evolve, it holds promising potential to augment medical research in a manner that is ethical, equitable, and patient-centric.
Topics: Humans; Artificial Intelligence; Hospitals; Biomedical Research; Exercise; Writing
PubMed: 38028967
DOI: 10.14797/mdcvj.1290 -
Asian Nursing Research Dec 2022To define school nurse-parent partnerships in school health care for children with type 1 diabetes (T1D) and determine its attributes using a hybrid model. (Review)
Review
PURPOSE
To define school nurse-parent partnerships in school health care for children with type 1 diabetes (T1D) and determine its attributes using a hybrid model.
METHODS
This method involves a three-phase process: theoretical, fieldwork, and analytical. A literature review was conducted during the theoretical phase. A literature search of articles from January 1991 to February 2020 was conducted using relevant electronic databases. Eighty-three articles that met the inclusion criteria were completely read. Fieldwork data were collected through individual interviews from February to July 2019 in South Korea. In the fieldwork phase, interviews were conducted individually with 22 mothers of students with T1D and 20 school nurses recruited by purposeful sampling. Inductive content analysis was conducted. The findings from the theoretical phase were integrated with those from the fieldwork phase, and the final concept was derived.
RESULTS
School nurse-parent partnership in school health care for children with T1D has been defined as an interactive process of maintaining a balanced responsibility and providing tailored care to meet needs by establishing trusting relationships and communicating transparently and openly. This analysis yielded four attributes: trusting relationships, transparent and open communication, balanced responsibility, and providing tailored care to meet needs-this entails providing nursing actions by advocating for students and performing a negotiated role together or individually for student and family.
CONCLUSION
The findings of this study add to the importance of an attribute of balancing responsibility for partnership in school health care. The results show that this partnership could contribute to the development of a scale, theory, and nursing intervention in school health care for children with T1D.
Topics: Female; Humans; Child; Diabetes Mellitus, Type 1; Delivery of Health Care; Mothers; Students; Nurses
PubMed: 36375806
DOI: 10.1016/j.anr.2022.11.001 -
Frontiers in Nutrition 2022The adoption of supplementary nutrition information, i.e., front-of-pack labeling (FOPL), on pre-packed food products is advocated as a tool to improve the consumers'... (Review)
Review
The adoption of supplementary nutrition information, i.e., front-of-pack labeling (FOPL), on pre-packed food products is advocated as a tool to improve the consumers' knowledge of the nutrient content or the nutritional quality of foods, but also to drive products reformulation by the food industry. Ultimately, FOPL should help people to select foods in order to compose an overall balanced diet, which is essential for health. However, the extent to which the different FOPL systems proposed in the European Union (EU) (interpretative or informative) are effectively able to convey the information useful to improve both food choices and dietary habits of the consumers is still under debate and needs to be analyzed in detail. The use of 3 FOPL schemes proposed within the EU (Nutri-Score, Keyhole and NutrInform Battery) to compare products available on the Italian market within different food categories, highlights some critical issues: (1) different FOPL provide to consumers different kinds of information; (2) systems based on similar theoretical approaches can provide conflicting information; (3) the algorithms on which interpretative FOPL are based can give the same summary information for products differing in nutrient composition, impact on the overall dietary balance and therefore on the health of people with different characteristics, physiological/pathological conditions, and nutritional requirements; (4) on the other hand, products with similar nutrient composition can obtain different interpretative FOPL; (5) informative systems are generally more complex and require greater both attention and knowledge from the consumer; (6) FOPL based on 100 g of product overlook the role of portion (and frequency of consumption) in determining the nutrient intake without informing on the contribution of a single food to the overall diet; (7) FOPL based on scoring systems could promote the reformulation of selected products, especially with a composition very close to the threshold limits; (8) for the portion-based informative FOPL systems, the incentive for reformulation could essentially involve the reduction of portion size. Finally, the importance of nutritional education interventions, which are required to encourage the use by consumers of informative FOPL systems, cannot be neglected to improve the quality of diets regardless of the FOPL used.
PubMed: 36061903
DOI: 10.3389/fnut.2022.963592 -
NeuroImage Dec 2021Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience.... (Review)
Review
Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective.
Topics: Connectome; Humans; Machine Learning; Magnetic Resonance Imaging; Mental Processes; Models, Statistical; Neuroimaging; Neurosciences; Reproducibility of Results
PubMed: 34648960
DOI: 10.1016/j.neuroimage.2021.118649 -
Diagnostics (Basel, Switzerland) Dec 2016Fatty acids, as structural components of membranes and inflammation/anti-inflammatory mediators, have well-known protective and regulatory effects. They are studied as... (Review)
Review
Fatty acids, as structural components of membranes and inflammation/anti-inflammatory mediators, have well-known protective and regulatory effects. They are studied as biomarkers of pathological conditions, as well as saturated and unsaturated hydrophobic moieties in membrane phospholipids that contribute to homeostasis and physiological functions. Lifestyle, nutrition, metabolism and stress-with an excess of radical and oxidative processes-cause fatty acid changes that are examined in the human body using blood lipids. Fatty acid-based membrane lipidomics represents a powerful diagnostic tool for assessing the quantity and quality of fatty acid constituents and also for the follow-up of the membrane fatty acid remodeling that is associated with different physiological and pathological conditions. This review focuses on fatty acid biomarkers with two examples of recent lipidomic research and health applications: (i) monounsaturated fatty acids and the analytical challenge offered by hexadecenoic fatty acids (C16:1); and (ii) the cohort of 10 fatty acids in phospholipids of red blood cell membranes and its connections to metabolic and nutritional status in healthy and diseased subjects.
PubMed: 28025506
DOI: 10.3390/diagnostics7010001