Journal articles: 'Healthcare resistance'

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Essex, Ryan. "Resistance in health and healthcare." Bioethics 35, no. 5 (March 8, 2021): 480–86. http://dx.doi.org/10.1111/bioe.12862.

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Pugliese, Gina, and Martin S. Favero. "Vancomycin Resistance Outside the Healthcare Setting." Infection Control & Hospital Epidemiology 18, no. 10 (October 1997): 729. http://dx.doi.org/10.1017/s0195941700000709.

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Waring, Justin J., and Simon Bishop. "Lean healthcare: Rhetoric, ritual and resistance." Social Science & Medicine 71, no. 7 (October 2010): 1332–40. http://dx.doi.org/10.1016/j.socscimed.2010.06.028.

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Winter, George. "Antibiotic resistance." Journal of Prescribing Practice 2, no. 8 (August 2, 2020): 430–31. http://dx.doi.org/10.12968/jprp.2020.2.8.430.

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This month, George Winter discusses how healthcare professionals are still reluctant to address the growing issue of antibiotic resistance, and examines the key factors that are contributing to this ongoing issue

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Ameri, M., L. Suarez, B. Miles, CF Michie, and J. Abdul. "Antimicrobial resistance: An unrelenting enemy." Global Journal of Medical and Clinical Case Reports 9, no. 1 (January 24, 2022): 008–14. http://dx.doi.org/10.17352/2455-5282.000147.

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Antimicrobial Resistance (AMR) poses an increasing threat to global public health and is projected to be one of the greatest challenges of healthcare in the future as the costs of healthcare, morbidity, and mortality will increase. AMR is likely to complicate many routine procedures such as elective surgery in the future. Together, healthcare professionals need to be aware of the significance antimicrobial resistance poses and make changes needed to mitigate the danger as a result of one of the most important developments in medicine.

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Chaibi, Asma, and Imed Zaiem. "Doctor Resistance of Artificial Intelligence in Healthcare." International Journal of Healthcare Information Systems and Informatics 17, no. 1 (January 1, 2022): 1–13. http://dx.doi.org/10.4018/ijhisi.315618.

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Artificial intelligence (AI) has revolutionized healthcare by enhancing the quality of patient care. Despite its advantages, doctors are still reluctant to use AI in healthcare. Thus, the authors' main objective is to obtain an in-depth understanding of the barriers to doctors' adoption of AI in healthcare. The authors conducted semi-structured interviews with 11 doctors. Thematic analysis as chosen to identify patterns using QSR NVivo (version 12). The results showed that the barriers to AI adoption are lack of financial resources, need for special training, performance risk, perceived cost, technology dependency, need for human interaction, and fear of AI replacing human work.

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Longoni, Chiara, Andrea Bonezzi, and Carey K. Morewedge. "Resistance to Medical Artificial Intelligence." Journal of Consumer Research 46, no. 4 (May 3, 2019): 629–50. http://dx.doi.org/10.1093/jcr/ucz013.

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Abstract Artificial intelligence (AI) is revolutionizing healthcare, but little is known about consumer receptivity to AI in medicine. Consumers are reluctant to utilize healthcare provided by AI in real and hypothetical choices, separate and joint evaluations. Consumers are less likely to utilize healthcare (study 1), exhibit lower reservation prices for healthcare (study 2), are less sensitive to differences in provider performance (studies 3A–3C), and derive negative utility if a provider is automated rather than human (study 4). Uniqueness neglect, a concern that AI providers are less able than human providers to account for consumers’ unique characteristics and circumstances, drives consumer resistance to medical AI. Indeed, resistance to medical AI is stronger for consumers who perceive themselves to be more unique (study 5). Uniqueness neglect mediates resistance to medical AI (study 6), and is eliminated when AI provides care (a) that is framed as personalized (study 7), (b) to consumers other than the self (study 8), or (c) that only supports, rather than replaces, a decision made by a human healthcare provider (study 9). These findings make contributions to the psychology of automation and medical decision making, and suggest interventions to increase consumer acceptance of AI in medicine.

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Simcock, Mathew, Pedram Sendi, Bruno Ledergerber, Tamara Keller, Jörg Schüpbach, Manuel Battegay, Huldrych F. Günthard, et al. "A Longitudinal Analysis of Healthcare Costs after Treatment Optimization following Genotypic Antiretroviral Resistance Testing: Does Resistance Testing pay off?" Antiviral Therapy 11, no. 3 (April 1, 2005): 305–14. http://dx.doi.org/10.1177/135965350601100305.

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Objective To assess the impact of antiretroviral therapy optimized by genotypic antiretroviral resistance testing (GRT) on healthcare costs over a 2-year period in patients after antiretroviral treatment failure. Study design Non-randomized, prospective, tertiary care, clinic-based study. Patients One-hundred and forty-two HIV patients enrolled in the ‘ZIEL’ study and the Swiss HIV Cohort Study who experienced virological treatment failure. Methods For all patients GRT was used to optimize the antiretroviral treatment regimen. All healthcare costs during 2 years following GRT were assessed using micro-costing. Costs were separated into ART medication costs and healthcare costs other than ART medication (that is, non-ART medication costs, in-patient costs and ambulatory [out-patient] costs). These cost estimates were then split into four consecutive 6-month periods (period 1–4) and the accumulated cost for each period was calculated. Univariate and multivariate regression modelling techniques for repeated measurements were applied to assess the changes of healthcare costs over time and factors associated with healthcare costs following GRT. Results Overall healthcare costs after GRT decreased over time and were significantly higher in period 1 (32%; 95% confidence interval [CI]: 18–47) compared with period 4. ART medication costs significantly increased by 1,017 (95% CI: 22–2,014) Swiss francs (CHF) from period 1–4, whereas healthcare costs other than ART medication costs decreased substantially by a factor of 3.1 (95% CI: 2.6–3.7) from period 1 to period 4. Factors mostly influencing healthcare costs following GRT were AIDS status, costs being 15% (95% CI: 6–24) higher in patients with AIDS compared with patients without AIDS, and baseline viral load, costs being 12% (95% CI: 6–17) higher in patients with each log increase in plasma RNA. Conclusions Optimized antiretroviral treatment regimens following GRT lead to a reduction of healthcare costs in patients with treatment failure over 2 years. Patients in a worse health state (that is, a positive AIDS status and high baseline viral load) will experience higher overall costs.

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Mohammed, Shafii, and Lisa Gorski. "Antimicrobial Resistance and Antimicrobial Stewardship in Home Healthcare." Home Healthcare Now 39, no. 5 (September 2021): 238–46. http://dx.doi.org/10.1097/nhh.0000000000001012.

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Landaeta, Rafael E., Ji Hyon Mun, Ghaith Rabadi, and David Levin. "Identifying sources of resistance to change in healthcare." International Journal of Healthcare Technology and Management 9, no. 1 (2008): 74. http://dx.doi.org/10.1504/ijhtm.2008.016849.

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Mareš, Jiří. "Resistance of health personnel to changes in healthcare." Kontakt 20, no. 3 (October 12, 2018): e262-e272. http://dx.doi.org/10.1016/j.kontakt.2018.04.002.

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Lindsay, Jodi A. "Transmission of antimicrobial resistance in resource-poor healthcare." Trends in Microbiology 23, no. 2 (February 2015): 69–70. http://dx.doi.org/10.1016/j.tim.2015.01.001.

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Ellen, Moriah E., Ruth Shach, and Saritte Perlman. "Exploring community healthcare providers’ perceptions on antimicrobial resistance." Journal of Global Antimicrobial Resistance 18 (September 2019): 215–22. http://dx.doi.org/10.1016/j.jgar.2019.02.010.

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Yezli, Saber, and Han Li. "Antibiotic resistance amongst healthcare-associated pathogens in China." International Journal of Antimicrobial Agents 40, no. 5 (November 2012): 389–97. http://dx.doi.org/10.1016/j.ijantimicag.2012.07.009.

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Lake, Jason G., Lindsey M. Weiner, Aaron M. Milstone, Lisa Saiman, Shelley S. Magill, and Isaac See. "Pathogen Distribution and Antimicrobial Resistance Among Pediatric Healthcare-Associated Infections Reported to the National Healthcare Safety Network, 2011–2014." Infection Control & Hospital Epidemiology 39, no. 1 (December 18, 2017): 1–11. http://dx.doi.org/10.1017/ice.2017.236.

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OBJECTIVETo describe pathogen distribution and antimicrobial resistance patterns for healthcare-associated infections (HAIs) reported to the National Healthcare Safety Network (NHSN) from pediatric locations during 2011–2014.METHODSDevice-associated infection data were analyzed for central line-associated bloodstream infection (CLABSI), catheter-associated urinary tract infections (CAUTI), ventilator-associated pneumonia (VAP), and surgical site infection (SSI). Pooled mean percentage resistance was calculated for a variety of pathogen-antimicrobial resistance pattern combinations and was stratified by location for device-associated infections (neonatal intensive care units [NICUs], pediatric intensive care units [PICUs], pediatric oncology and pediatric wards) and by surgery type for SSIs.RESULTSFrom 2011 to 2014, 1,003 hospitals reported 20,390 pediatric HAIs and 22,323 associated pathogens to the NHSN. Among all HAIs, the following pathogens accounted for more than 60% of those reported: Staphylococcus aureus (17%), coagulase-negative staphylococci (17%), Escherichia coli (11%), Klebsiella pneumoniae and/or oxytoca (9%), and Enterococcus faecalis (8%). Among device-associated infections, resistance was generally lower in NICUs than in other locations. For several pathogens, resistance was greater in pediatric wards than in PICUs. The proportion of organisms resistant to carbapenems was low overall but reached approximately 20% for Pseudomonas aeruginosa from CLABSIs and CAUTIs in some locations. Among SSIs, antimicrobial resistance patterns were similar across surgical procedure types for most pathogens.CONCLUSIONThis report is the first pediatric-specific description of antimicrobial resistance data reported to the NHSN. Reporting of pediatric-specific HAIs and antimicrobial resistance data will help identify priority targets for infection control and antimicrobial stewardship activities in facilities that provide care for children.Infect Control Hosp Epidemiol 2018;39:1–11

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Shrief, Raghdaa, Reem Mohsen El-Kholy, Mohamed Annies Rizk, and Maysaa El-Sayed Zaki. "revalence of Tetracycline Resistant Genes in Staphylococcus aureus Isolates from Surgical Site Infections Egypt." Biosciences, Biotechnology Research Asia 16, no. 2 (June 25, 2019): 229–50. http://dx.doi.org/10.13005/bbra/2740.

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The aim of the present study was to investigate the prevalence of tetracycline resistance genes among isolated S. aureus from healthcare associated surgical site infections. The present study included 350 clinical samples from healthcare associated surgical site infections. Identified S. aureus strains were subjected to antimicrobial susceptibility testing, detection of methicillin resistance by cefoxitin disc and molecular study of mecA and tet genes that were carried out by polymerase chain reaction and multiplex polymerase chain reaction, respectively. There were high resistance rates of isolated S. aureus to gentamicin (71.2%), kanamycin (66.5%) and ceftazidime (41.8%). Resistances to tetracycline, doxycycline and minocycline were 60.6%, 56.5% and 45.3%, respectively. In the comparison between MRSA and MSSA as regards antibiotics resistance, there was a significant increase in resistance to tetracycline, doxycycline, minocycline (P=0.0001) and erythromycin (P=0.01) among MRSA strains compared to MSSA. The tetracycline resistant genes detected were tetK (92.3%) and tetM (25.2%). Combined genes were detected in 22.3% of S. aureus. None of tetracycline isolates had tetL or tetO gene. There was significant higher frequency of telK, tetM and combined genes among MRSA compared to MSSA (P=0.0001). The present study highlights the prevalence of multiple antibiotics resistance among clinical isolates of S. aureus associated with healthcare associated infections. The resistance increases among methicillin resistant S. aureus. The resistance to tetracycline, minocycline and doxycycline were common. The common genetic basis of the resistance to tetracycline was the tetK and tetM genes.

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Sarvananda, L., and Amal D Premarathne. "The Growing Of Antibiotic Resistance: A Short Viewpoint." Pharmaceutics and Pharmacology Research 5, no. 3 (March 6, 2022): 01–02. http://dx.doi.org/10.31579/2693-7247/068.

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The discovery of antibiotics becomes one of the maximum groundbreaking improvements of drugs. This healthcare staple, liable for treating illnessesthat when had been incurable, is now turning into much less and much lesspowerful due to antibiotic resistance. The microorganism accountable can emerge as immune to this medicinal drug through genetic mutation through replica or from other microorganism via transformation, transduction, or conjugation. It is critical to recognize the strategies wherein antibiotic resistance takes place to formulate a plan of assault in this healthcare disaster. The biggest populace of antibiotic customers in the U.S. is livestock, as medicinal drug is given preventatively and in huge portions in order to shield the herd. Knowing this, efforts are being made to fight it. As of now the two primary techniques to relieve this urgentbe counted are to both create new antibiotics to outrun the rapid mutations of the microorganism or to reduce the quantity of antibiotics fed on which could pause or gradual the rate of antibiotic resistance. Both of those methods include disadvantages; but those efforts are hired for loss of a higher opportunity. It is obvious that we're getting ready to a pharmaceutical disaster each nationally and globally and extra exploration is wanted to benefit manage of antibiotic resistance.

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Masia, Maria Dolores, and Marco Dettori. "Antimicrobial Resistance, Healthcare-Associated Infections, and Environmental Microbial Contamination." Healthcare 10, no. 2 (January 27, 2022): 242. http://dx.doi.org/10.3390/healthcare10020242.

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Mudur, G. "Indian plan for rural healthcare providers encounters more resistance." BMJ 346, mar27 1 (March 27, 2013): f1967. http://dx.doi.org/10.1136/bmj.f1967.

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Чернавский, Александр, Aleksandr Chernavskiy, Игорь Петров, Igor' Petrov, А. Гаврилова, A. Gavrilova, М. Чернавский, and M. Chernavskiy. "Empirical study of stress resistance among public healthcare workers." Actual problems in dentistry 12, no. 3 (September 25, 2016): 107–12. http://dx.doi.org/10.18481/2077-7566-2016-12-3-107-112.

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Ngafeeson, Madison N., and Vishal Midha. "An exploratory study of user resistance in healthcare IT." International Journal of Electronic Finance 8, no. 1 (2014): 74. http://dx.doi.org/10.1504/ijef.2014.064003.

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Lillie, Patrick, Hiten Thaker, Peter Moss, Joy Baruah, Lorraine Cullen, Damien Taylor, and Gavin Barlow. "Healthcare Associated Discitis in the Era of Antimicrobial Resistance." JCR: Journal of Clinical Rheumatology 14, no. 4 (August 2008): 234–37. http://dx.doi.org/10.1097/rhu.0b013e318181addd.

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Aziz, Ann-Marie. "The role of healthcare strategies in controlling antibiotic resistance." British Journal of Nursing 22, no. 18 (October 2013): 1066–74. http://dx.doi.org/10.12968/bjon.2013.22.18.1066.

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Torres-Caycedo, María Inés, Lisbeth Teresa Castro-Gutiérrez, Carlos Fernando Prada-Quiroga, and Diana Paola López-Velandia. "Resistencia a antibióticos: Origen, evolución e infecciones asociadas a la atención en salud." Salud Uninorte 34, no. 2 (February 15, 2019): 494–505. http://dx.doi.org/10.14482/sun.34.2.615.32.

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Maillard, Jean-Yves. "Emergence of bacterial resistance to microbicides and antibiotics." Microbiology Australia 31, no. 4 (2010): 159. http://dx.doi.org/10.1071/ma10159.

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Public awareness of the role of microorganisms in infection and spoilage and the role of the media in highlighting poor hygiene and the failure of healthcare settings in preventing hospital-acquired infections, have fuelled the use of products containing one or several microbicides in the healthcare environment but also at home. The number of such products with a microbicidal claim is increasing rapidly, although their impact on the microbial flora, notably in terms of emerging antimicrobial resistance has not been documented. With increasing evidence that microbicides can lead to bacterial resistance and cross-resistance to antibiotics, concerns have been expressed regarding the indiscriminate used of microbicidal products. This review aims to provide up-to-date information on the use of microbicides in the healthcare settings.

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Salawu, Kazeem Joshua, Wafa Hammedi, and Annick Castiaux. "What about Passive Innovation Resistance? Exploring User’s Resistance to Technology in the Healthcare Sector." Journal of Innovation Economics & Management 30, no. 3 (2019): 17. http://dx.doi.org/10.3917/jie.pr1.0055.

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Kallen, Alexander J., Alicia I. Hidron, Jean Patel, and Arjun Srinivasan. "Multidrug Resistance among Gram-Negative Pathogens That Caused Healthcare-Associated Infections Reported to the National Healthcare Safety Network, 2006–2008." Infection Control & Hospital Epidemiology 31, no. 05 (May 2010): 528–31. http://dx.doi.org/10.1086/652152.

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We evaluated isolates of Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii that were reported to the National Healthcare Safety Network from January 2006 through December 2008 to determine the proportion that represented multidrug-resistant phenotypes. The pooled mean percentage of resistance varied by the definition used; however, multidrug resistance was relatively common and widespread.

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Kwarteng Owusu, Victor, and Ales Gregar. "Measuring the antecedents of turnover intentions: Perspectives of private healthcare employees in a less-developed economy." Problems and Perspectives in Management 19, no. 4 (November 10, 2021): 232–47. http://dx.doi.org/10.21511/ppm.19(4).2021.19.

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This study sets out to investigate the antecedents of turnover intentions, using the private healthcare employees in an emerging economy (Ghana) as a benchmark. Even though myriad studies have been conducted on the aforementioned topic, yet, there are scant investigations on how employees of private healthcare institutions relate towards turnover intentions, specifically in a developing economy context. Therefore, this study draws on extant literature and subsequently proposes a hypothetical argument on the effect of training satisfaction, benefits and incentives on employee turnover intentions as well as resistance to change while establishing the nexus between turnover intentions and resistance to change. Both paper and web-based (online) questionnaires were gauged from employees of private healthcare organizations in Ghana. Data were analyzed by partial least square structural equation modeling (PLS-SEM) on a sample of 544 employees of private healthcare institutions. The findings indicate that training satisfaction, benefits and incentives have a positive impact on an employee’s turnover intentions. Moreover, employee’s resistance to change is influenced by both training satisfaction and benefits and incentives. Further, the investigation established that employee’s resistance to change influences employee turnover intentions. The thoughtful mechanisms of how the running of private healthcare institutions in Ghana can be enhanced are expanded by the empirical results obtained through how employees can be satisfied by training and the application of rewards to reduce turnover. Moreover, administrators of private healthcare organizations are forewarned of the implications of employees’ resistance to change and its effect on employee turnover intentions. Acknowledgment This study was supported by Tomas Bata University in Zlín, through IGA/FaME/2020/003 “Training and development programs and the consequence on employee’s commitment, satisfaction and organizational performance: analysis from Czech public service sector”.

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Longoni, Chiara, Andrea Bonezzi, and Carey K. Morewedge. "Resistance to medical artificial intelligence is an attribute in a compensatory decision process: response to Pezzo and Beckstead (2020)." Judgment and Decision Making 15, no. 3 (May 2020): 446–48. http://dx.doi.org/10.1017/s1930297500007233.

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AbstractIn Longoni et al. (2019), we examine how algorithm aversion influences utilization of healthcare delivered by human and artificial intelligence providers. Pezzo and Beckstead’s (2020) commentary asks whether resistance to medical AI takes the form of a noncompensatory decision strategy, in which a single attribute determines provider choice, or whether resistance to medical AI is one of several attributes considered in a compensatory decision strategy. We clarify that our paper both claims and finds that, all else equal, resistance to medical AI is one of several attributes (e.g., cost and performance) influencing healthcare utilization decisions. In other words, resistance to medical AI is a consequential input to compensatory decisions regarding healthcare utilization and provider choice decisions, not a noncompensatory decision strategy. People do not always reject healthcare provided by AI, and our article makes no claim that they do.

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Lu, Wei-Chih, I.-Ching Tsai, Kuan-Chung Wang, Te-Ai Tang, Kuan-Chen Li, Ya-Ci Ke, and Peng-Ting Chen. "Innovation Resistance and Resource Allocation Strategy of Medical Information Digitalization." Sustainability 13, no. 14 (July 14, 2021): 7888. http://dx.doi.org/10.3390/su13147888.

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Healthcare industries are facing an enormous flow of medical records due to the progression of information technology and the trend of digital transformation. Thus, medical information digitalization is a huge digital dataset that can be utilized to benefit healthcare systems and patients. While many studies focus on the application of the digitalized medical information in the healthcare field, only a few mentioned its resistance. The theoretical background depicts a comprehensive overview of medical information digitalization and the barriers in previous literature. This study emphasized the interaction of medical information digitalization barriers and applies the importance-resistance analysis model (IRA) to identify the resistant factors overcoming strategy. It also clarifies the pathway to eliminating the innovation resistance and reveals the interaction of medical information digitalization barriers. The acquisition, management, and application of medical information digitalization are the key foundation of medical technology innovation, digital transformation, and the application of artificial intelligence. This work can reduce the limitation of a narrow healthcare context. This study helps healthcare industries to clarify and solve barriers and realizes the innovation and application of medical information digitalization. In the long term, the results provide a basis for the future development direction of medical information digitalization and affect the medical industry.

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Putri Shareen Rosman, Tavasuria Elangovan, Wan Nurul Hidayah Wan Anuar, and Nur Atirah Hasmi. "Biocide resistance." Journal of Advanced Research in Applied Sciences and Engineering Technology 24, no. 1 (October 7, 2021): 63–67. http://dx.doi.org/10.37934/araset.24.1.6367.

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The pandemic COVID-19 that the world are facing today has led to high usage of disinfectants and routinely used in the community. However, the extensive usage of biocides for disinfection could lead to antimicrobial resistance (AMR). Antimicrobial resistance has become the major caused that contributes increase in morbidity and mortality rate. The wide scale use of biocides creates selective stress that will favor bacteria in expressing resistance mechanisms and their dissemination. Some biocides have the potential to create cross resistance with the antibiotics and developing co-resistance to spread the Antimicrobial resistance (AMR). In this review, the author will discuss on the potential threat in the healthcare caused by the biocides that could drive the AMR to become worse.

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Renkens, José, Els Rommes, and Maria van den Muijsenbergh. "Refugees' Agency: On Resistance, Resilience, and Resources." International Journal of Environmental Research and Public Health 19, no. 2 (January 12, 2022): 806. http://dx.doi.org/10.3390/ijerph19020806.

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This study set out to answer the question ‘Which kinds of agency do refugees perform when dealing with mental health problems of themselves and their children?’. Aiming to gain more insight in why it seems harder for refugee parents and minors than for the native population to talk to health professionals about their mental health and wellbeing, we combined two theoretical notions of agency to investigate a broad spectrum of informants’ behaviour. We conducted 25 interviews with 30 refugees from 8 countries (Syria, Yemen, Iran, Afghanistan, Armenia, Eritrea, Turkish Kurdistan, Vietnam), whose Dutch residence permit varied from 26 years to less than one year. Data were analysed through open and axial coding, followed by pattern analyses. Although sometimes refugees seek (mental) healthcare, at other times they show agency by doing ‘nothing’ or by deliberately using distracting activities to deal with severe stress. Making use of resources available to them, oftentimes refugees show agency in ways that are less visible to healthcare professionals, by surviving, showing resilience, and suffering. In these cases, we think healthcare for refugees should intervene in a non-medical way, e.g., by supporting them to obtain resources that help refugees to (re)gain agency.

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Ledda, Caterina, Diana Cinà, Serena Matera, Nicola Mucci, Massimo Bracci, and Venerando Rapisarda. "High HOMA-IR Index in Healthcare Shift Workers." Medicina 55, no. 5 (May 22, 2019): 186. http://dx.doi.org/10.3390/medicina55050186.

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Background and objectives: Evidence shows that shift work may be correlated with insulin resistance (IR). Therefore its estimation in clinical and prevention practice is of great significance. A cross-sectional study was performed to examine the Homeostasis Model Assessment-Insulin Resistance (HOMA-IR) Index among healthcare shift workers (HCSW). Materials and Methods: A total of 272 healthcare workers (HCWs) were invited to participate in the study within an occupational surveillance framework, 137 were HCSW while 135 were healthcare non-shift workers (HCNSW). Fasting glucose, insulin, and HOMA-IR Index were evaluated in each participant and correlated with shift workers. Results: Indicators of glucose metabolism were significantly higher in HCSW p < 0.001, and logistic regression analysis confirmed a significant positive association between increased values of HOMA-IR Index and shift workers (p < 0.05). Conclusions: Shift work could be a risk factor in developing insulin resistance and metabolic syndrome.

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Ojeaburu, Sandra. "Birthing Knowledge Production as Resistance." Undergraduate Journal of Service Learning & Community-Based Research 10 (November 12, 2020): 69–83. http://dx.doi.org/10.56421/ujslcbr.v10i0.305.

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ABSTRACT How does risk of mortality during childbirth become internalized and embodied in Black communities? While mainstream news articles aim to bring attention to inadequacies in Black maternal healthcare, few ethnographies elucidate the effect that these risk factors have on Black women’s psychosocial health and the support networks they turn to in order to mitigate risk. My ethnography analyzes the effects of institutional racism on maternal mortality risk factors, specifically toxic stress and grounds Black maternal health in the context of a burgeoning doula movement in Mississippi. Through tracing the psychosocial and emotional support networks of single Black mothers on WIC and working Black mothers, I elucidate several inadequacies in healthcare models of maternal care. I identify the framework of medicalization in pregnancy care that arose in Mississippi in 1920, as a way to dismantle existing Black birth work communities, mitigate infant mortality risk, and subsequently stratified birthing knowledge production. Through an analysis of midwifery and doula work in Mississippi, this article traces the displacement of Black midwives and other nonmedical Black birth workers in Mississippi and the distrust these communities harbor towards hospitals in the present-day. My article primarily aims to bring equity to Black birth workers modes of knowledge production. It explores intergenerational distrust and fear in the context of Black maternal health in Mississippi. First, I trace the unequal landscape of birthing care for Black women in Mississippi from the development of public health in 1920 to the current locales of clinical care. Next, I emphasize intergenerational trauma as contributing to stress for Black expectant mothers and the need for psychosocial support. Finally, I present findings that recommend integration and standardization of doulas in the healthcare system and centering maternal psychosocial support in communities.

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KŁOS, Marta, Monika Pomorska-Wesołowska, Dorota Romaniszyn, Agnieszka Chmielarczyk, and Jadwiga Wojkowska-Mach. "Healthcare-Associated Infections: Enterobacteriaceae Bloodstream Infections in the ICU Settings." Infection Control & Hospital Epidemiology 41, S1 (October 2020): s246—s247. http://dx.doi.org/10.1017/ice.2020.805.

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Background: Bloodstream infections (BSIs) are one of the most frequently observed hospital-acquired infections (HAIs). Objectives: We aimed to describe the epidemiology and drug resistance of hospital-acquired Enterobacteriaceae BSIs and to check for any correlation with the type of hospital care. Methods: In 2015–2018, 333 Enterobacteriaceae isolates were collected from hospitalized internal medicine and surgical patients. The drug-resistance testing was conducted according to the EUCAST recommendations, using the disc-diffusion method to determine resistance to penicillin, cephalosporins, carbapenems, aminoglycosides, fluoroquinolones, and sulfamethoxazole with trimethoprim. Tests confirming the presence of extended-spectrum β-lactamases (ESBLs) and KPC, NDM, and OXA-48 carbapenemases were performed. We determined the minimum inhibitory concentration (MIC) values (mg/L) for selected antibiotics. To detect the resistance genes, a single PCR reaction, a multiplex PCR, and a real-time PCR were conducted. Results: The prevalence rate of Enterobacteriaceae bacilli in BSIs was 23.5%. Penicillin resistance remained at a very high level of almost 100%, with only the piperacillin-tazobactam resistance remaining at 19%–22%. The same was true for cephalosporins: the bacilli have only shown a high susceptibility to cefoperazone with sulbactam (4%–14% of them were resistant). Ciprofloxacin (53%–62%) and sulfamethoxazole with trimethoprim (48–55%) have proven highly resistant. Carbapenems were the only antibiotics with susceptibility at 98%–99%. No difference was found between the types of hospital care (surgical vs nonsurgical) and the levels of antimicrobial resistance in the studied Enterobacteriaceae isolates (Table 1). Conclusions: The high prevalence of Enterobacteriaceae bacilli in BSI is particularly worrying, as is the high rate of resistance to cephalosporins and aminoglycosides, which are often used in the empirical therapy. Unfortunately, our results indicate the need to base the empirical therapy on carbapenems.Funding: This work was supported by a grant from Jagiellonian Univerity Medical School (No. N41/DBS/000053)Disclosures: None

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Gu, Mofan, Bruce Taylor, Harold A. Pollack, John A. Schneider, and Nickolas Zaller. "A pilot study on COVID-19 vaccine hesitancy among healthcare workers in the US." PLOS ONE 17, no. 6 (June 15, 2022): e0269320. http://dx.doi.org/10.1371/journal.pone.0269320.

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To explore the attitude towards COVID-19 vaccination among healthcare workers in the US, we surveyed three groups of individuals (essential non-healthcare workers, general healthcare workers, and correctional healthcare workers). We found surprisingly high portions of healthcare workers with COVID-19 vaccine hesitancy/resistance, with 23% of correctional healthcare workers and 17% general healthcare workers (as compared to 12%) refusing to be vaccinated against COVID-19. Multivariate regression models suggest that current season flu vaccination (aOR = 3.34), relying on employer for COVID-19 information (aOR = 3.69), and living in the Midwest (aOR = 5.04) to be strongly associated with COVID-19 vaccine acceptance among essential workers and general healthcare workers. Current season flu vaccination (aOR = 7.52) is also strongly associated with COVID-19 vaccine acceptance among correctional healthcare workers. Potential mechanisms of vaccine hesitancy/resistance among healthcare workers involves low health literacy and employer mistrust. Our findings are highly relevant as we try to reach COVID-19 vaccination goals in the US.

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Jayadi, Tejo. "BIOFILMS AND ANTIBIOTIC RESISTANCE." Berkala Ilmiah Kedokteran Duta Wacana 6, no. 2 (April 18, 2022): 26. http://dx.doi.org/10.21460/bikdw.v6i2.464.

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<p>The physician and health practitioner’s attention and alertness to biofilm existence and the consequences of biofilm in the biotic and abiotic environment are important to improve hygiene practice, rational antibiotic prescription, controlling the spread and emergence of emergency antibiotic resistance in healthcare facilities and community. The majority of chronic persistence and recurrent infection because of antibiotic resistance is biofilm infection, so needed precision and power alternative approach of management and therapy.</p>

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Snoek, Frank J., Lawrence Fisher, William H. Polonsky, Heather Stuckey, Danielle Hessler, Tricia Tang, Norbert Hermanns, et al. "Overcoming psychological insulin resistance: A practical guide for healthcare professionals." Primary Care Diabetes 15, no. 3 (June 2021): 619–21. http://dx.doi.org/10.1016/j.pcd.2021.03.001.

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Muddassir, Maria, Almas Raza, Sadaf Munir, U. Basirat, O. Arshad ,. Dar, Mazia Shahid, S. Shoaib ,. Ahmed, S. Shamim, and S. Z. H. Naqvi. "Prevalence of Multidrug Resistance in Pseudomonas Aeruginosa in Healthcare Facilities." Pakistan Journal of Medical and Health Sciences 16, no. 9 (September 30, 2022): 5–9. http://dx.doi.org/10.53350/pjmhs221695.

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Pseudomonas aeruginosa is on the list of Gram-negative pathogens that are increasingly being counted as significant causes of nosocomial infections leading to significantly raised levels of morbidity and mortality. Life-threatening infections become more debilitating for those having a compromised immunity. The importance of Pseudomonas aeruginosa as a disease-causing microbe is enhanced through its increasing resistance to antibiotic drugs, the virulence factors plus its strength to adapt to wider environmental conditions. Pseudomonas aeruginosa possesses multiple acquired and intrinsic mechanisms providing resistance, often with augmented rates of resistance to multiple antimicrobial drugs. In the last decade, the global dissemination of the presumed ‘hazardous clones’ of multiple drug-resistant and extensively drug-resistant Pseudomonas aeruginosa have emerged as a serious threat to communal healthcare requiring extensive study and should be managed with determination and urgency. From the list of infections that are due to Gram-negative bacteria, Pseudomonas aeruginosa counts as a leading microbe causative for health-care-related infections in hospitalized individuals. In accordance with the guidelines by WHO, certain measures adopted in healthcare settings can help prevent transmission of multidrug-resistant Pseudomonas aeruginosa including hand hygiene (using alcohol-based solutions), contact precautions, cleanliness of the environment, isolation of patient (cohort or single room), plus surveillance. Keywords: Antibiotic resistance, Nosocomial, Infections, Resistance mechanisms, Pseudomonas aeruginosa

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van Essen, Gerrit A. "Influenza vaccination of healthcare workers, oseltamivir resistance and prepandemic vaccination." Expert Review of Respiratory Medicine 2, no. 6 (December 2008): 703–5. http://dx.doi.org/10.1586/17476348.2.6.703.

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Oxford, J., and R. Kozlov. "Antibiotic resistance - a call to arms for primary healthcare providers." International Journal of Clinical Practice 67 (November 2013): 1–3. http://dx.doi.org/10.1111/ijcp.12334.

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Lutz, Philipp, Hans Dieter Nischalke, Benjamin Krämer, Felix Goeser, Dominik J. Kaczmarek, Stefan Schlabe, Marijo Parcina, et al. "Antibiotic resistance in healthcare-related and nosocomial spontaneous bacterial peritonitis." European Journal of Clinical Investigation 47, no. 1 (December 7, 2016): 44–52. http://dx.doi.org/10.1111/eci.12701.

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Pietsch, F., A. J. O'Neill, A. Ivask, H. Jenssen, J. Inkinen, A. Kahru, M. Ahonen, and F. Schreiber. "Selection of resistance by antimicrobial coatings in the healthcare setting." Journal of Hospital Infection 106, no. 1 (September 2020): 115–25. http://dx.doi.org/10.1016/j.jhin.2020.06.006.

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&NA;. "CDC PROMOTES CAMPAIGN TO PREVENT ANTIMICROBIAL RESISTANCE IN HEALTHCARE SETTINGS." Infectious Diseases in Clinical Practice 11, no. 3 (March 2002): 172. http://dx.doi.org/10.1097/00019048-200203000-00032.

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Chen See, Patrick, and Neil Baum. "Use of Botanicals in Modern Healthcare." Healthcare Administration Leadership & Management Journal 1, no. 1 (April 8, 2023): 27–30. http://dx.doi.org/10.55834/halmj.5949966089.

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As a result of the increase in demand for botanical products, modern healthcare providers need to become knowledgeable about these products. This article provides a brief review of the use of botanicals, what role these products may have in contemporary medicine, the importance of understanding the interactions between botanical and conventional medications, the resistance of physicians to prescribing botanicals, and the use and safety of botanical products.

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Westerhof, Robbin, and Lisanne de Boer. "Regional Supervision of Healthcare Institutions With a Focus on Antimicrobial Resistance." Infection Control & Hospital Epidemiology 41, S1 (October 2020): s371—s372. http://dx.doi.org/10.1017/ice.2020.1000.

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Background: Resistance to antibiotic drugs, also called antimicrobial resistance (AMR) is a serious threat to (public) health. Surveillance reports throughout the world show that formation and spread of highly resistant microorganisms (HRMOs) continues to be substantial. In The Netherlands, 10 regional collaborative networks on AMR have been established among healthcare institutions to mitigate the existing risks concerning HRMO by collaborative actions in antibiotic stewardship and infection prevention. Objective: We sought to determine whether the healthcare institutions in one of the regional collaborative networks in The Netherlands contribute adequately to reducing the risks of formation and/or spread of HRMO. Methods: The Health and Youth Care Inspectorate in The Netherlands visited 37 institutions in the region of Limburg (the southern province). The following healthcare sectors were included: hospitals (n = 5), rehabilitation clinics (n = 2), long-term care facilities (n = 5), homecare institutions (n = 4), mental healthcare institutions (n = 2), dental care clinics (n = 4), general practitioners (GPs; n = 10), municipal health services (n = 2) and healthcare facilities for mentally disabled people (n = 3). In each visit, 5 topics were addressed: antibiotic policy, infection prevention, information transfer, governance and collaboration in the region. Results and Conclusions: In general, the healthcare institutions had an adequate to good score. Good results were seen in antibiotic policy (ie, the use of diagnostic tools to avoid the use of antibiotics); information transfer among GPs and in homecare institutions; and infection prevention in homecare institutions and dental care clinics. Exceptions with inadequate scores were observed in several areas: absence of prescription guidance specifically for antibiotics in various sectors; infection prevention among GPs, and dental care clinics. In 4 cases (ie, 3 GPs and 1 dental care clinic), we stopped using the autoclave because of lack of proof of proper maintenance.Funding: NoneDisclosures: None

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Kusi, Joseph, Catherine Oluwalopeye Ojewole, Akinloye Emmanuel Ojewole, and Isaac Nwi-Mozu. "Antimicrobial Resistance Development Pathways in Surface Waters and Public Health Implications." Antibiotics 11, no. 6 (June 18, 2022): 821. http://dx.doi.org/10.3390/antibiotics11060821.

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Human health is threatened by antibiotic-resistant bacteria and their related infections, which cause thousands of human deaths every year worldwide. Surface waters are vulnerable to human activities and natural processes that facilitate the emergence and spread of antibiotic-resistant bacteria in the environment. This study evaluated the pathways and drivers of antimicrobial resistance (AR) in surface waters. We analyzed antibiotic resistance healthcare-associated infection (HAI) data reported to the CDC’s National Healthcare Safety Network to determine the number of antimicrobial-resistant pathogens and their isolates detected in healthcare facilities. Ten pathogens and their isolates associated with HAIs tested resistant to the selected antibiotics, indicating the role of healthcare facilities in antimicrobial resistance in the environment. The analyzed data and literature research revealed that healthcare facilities, wastewater, agricultural settings, food, and wildlife populations serve as the major vehicles for AR in surface waters. Antibiotic residues, heavy metals, natural processes, and climate change were identified as the drivers of antimicrobial resistance in the aquatic environment. Food and animal handlers have a higher risk of exposure to resistant pathogens through ingestion and direct contact compared with the general population. The AR threat to public health may grow as pathogens in aquatic systems adjust to antibiotic residues, contaminants, and climate change effects. The unnecessary use of antibiotics increases the risk of AR, and the public should be encouraged to practice antibiotic stewardship to decrease the risk.

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Rossi, Stefano, Massimo Calovi, and Matteo Tonelli. "Powder Coating for Healthcare Aluminum Packaging." Cosmetics 7, no. 2 (March 26, 2020): 20. http://dx.doi.org/10.3390/cosmetics7020020.

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Restrictive regulations concerning the toxicity of certain compounds and the use and disposal of solvents present in the liquid epoxy protection system have been analyzed in this work to evaluate powder coatings as an alternative in the protection of aerosol aluminum cans, which are employed in cosmetics and pharmaceutical product packaging. In this paper, the chemical resistance of polyester and mixed epoxy-polyester powder coatings is assessed, considering different aggressive environments employed in healthcare commercial products. The samples’ performances are also compared with the currently used liquid organic coatings. The pack test has been used to evaluate the protective system behavior in contact with both the liquid and the gaseous part of the cosmetic product. However, the visual observation, required by the test, enabled the highlight of only very evident degradation phenomena. The chemical resistance of the powder coatings has proved to be appropriate only for less aggressive environment, where the critical compounds are propellants, propane, butane and isobutane. When exposed to other environments containing alcohol, water and dimethyl ether, most samples have been susceptible to layer degradation phenomena. Polyester layers lose their corrosion protection properties. Epoxy systems, instead, result more performant than polyester resins, but they particularly suffer from the contact with dimethyl ether.

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Weiner-Lastinger, Lindsey M., Sheila Abner, Andrea L. Benin, Jonathan R. Edwards, Alexander J. Kallen, Maria Karlsson, Shelley S. Magill, et al. "Antimicrobial-resistant pathogens associated with pediatric healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network, 2015–2017." Infection Control & Hospital Epidemiology 41, no. 1 (November 25, 2019): 19–30. http://dx.doi.org/10.1017/ice.2019.297.

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AbstractObjective:To describe common pathogens and antimicrobial resistance patterns for healthcare-associated infections (HAIs) among pediatric patients that occurred in 2015–2017 and were reported to the Centers for Disease Control and Prevention’s National Healthcare Safety Network (NHSN).Methods:Antimicrobial resistance data were analyzed for pathogens implicated in central line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), ventilator-associated pneumonias (VAPs), and surgical site infections (SSIs). This analysis was restricted to device-associated HAIs reported from pediatric patient care locations and SSIs among patients <18 years old. Percentages of pathogens with nonsusceptibility (%NS) to selected antimicrobials were calculated by HAI type, location type, and surgical category.Results:Overall, 2,545 facilities performed surveillance of pediatric HAIs in the NHSN during this period. Staphylococcus aureus (15%), Escherichia coli (12%), and coagulase-negative staphylococci (12%) were the 3 most commonly reported pathogens associated with pediatric HAIs. Pathogens and the %NS varied by HAI type, location type, and/or surgical category. Among CLABSIs, the %NS was generally lowest in neonatal intensive care units and highest in pediatric oncology units. Staphylococcus spp were particularly common among orthopedic, neurosurgical, and cardiac SSIs; however, E. coli was more common in abdominal SSIs. Overall, antimicrobial nonsusceptibility was less prevalent in pediatric HAIs than in adult HAIs.Conclusion:This report provides an updated national summary of pathogen distributions and antimicrobial resistance patterns among pediatric HAIs. These data highlight the need for continued antimicrobial resistance tracking among pediatric patients and should encourage the pediatric healthcare community to use such data when establishing policies for infection prevention and antimicrobial stewardship.

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Shcherbakova, I. L., S. M. Megrelishvili, D. S. Kliachko, S. B. Sugarova, and L. V. Anosova. "Emotional burnout syndrome in healthcare professionals." Meditsinskiy sovet = Medical Council, no. 20 (November 19, 2022): 158–63. http://dx.doi.org/10.21518/2079-701x-2022-16-20-158-163.

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Currently, one of the most pressing concerns of labor psychology and healthcare is emotional burnout in healthcare professionals. During the COVID- 19 pandemic this condition has become very significant due to it takes a lot of physical, phychoemotional and ethical commitment of medical personnel. Emotional burnout is a syndrome that derives from chronic stress and leads to the depletion of personal, emotional, and energy resources of a person in the professional life. It is an dynamic sequential process and relevant to stress stages (the alarm stage, the resistance stage and the exhaustion stage). There are many various factors inducing the burnout syndrome: social, political, economic, bureaucratic, etc. In the process of studying this phenomenon, different models of emotional burnout were proposed. The most famous model is the three-part model of burnout by С. Maslach, which includes emotional exhaustion, depersonalization and a decrease in personal achievements. In Russia V. V. Boyko has been studying the burout phenomenon. There are three main stages of emotional burnout (alarm, resistance and exhaustion), which have a close connection to stress stages; each stage has a specific combination of symptoms. According to a number of authors, burnout syndrome is closely related to empathy, therefore, it is necessary to study the relationship between the level of empathy and the degree of emotional burnout in healthcare professionals for planning further psychological support for the prevention of this syndrome.

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Journal articles on the topic 'Healthcare resistance'

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